Aspects of the disclosure relate to providing a secure large language model data platform. The secure large language model uses a machine-learning large language model and gateway to prevent attacks and unauthorized access to enterprise-managed information and resources. The secure large language model may utilize pre-enrollment at a secure gateway providing a unique identification to each client. A private/public key pair may be generated and stored in the secure gateway database and large language model respectively. In some embodiments, a unique anonymization rule set may be generated and used for each client. Threat actors cannot query the large language model directly based on the pre-enrollment process. Unauthorized requests cannot be decrypted by the large language model due to missing paired keys.
A system is provided for wireless online processing using a peer to peer network. In particular, the system may comprise a plurality of wireless computing devices in nearby proximity to one another that may form the peer to peer (“P2P”) network through a shared wireless communication channel. The system may identify the network connection strengths of each of the plurality of wireless computing devices and subsequently designate one or more devices as the hubs of the P2P network. Each of the wireless computing devices may have one or more online processes to be completed through the network connections formed by the P2P network. The processes may be propagated to the devices within the P2P network, where the data used to complete the processes may be encrypted within the memory or storage devices of each of the computing devices.
Systems, computer program products, and methods are described herein for homomorphic ancillary document data encryption, data authentication, and data transfer. The present disclosure includes receiving an interaction event from a terminal device, receiving, upon a first condition where the resource transfer card comprises an embedded document card comprising at least one document data file, a network check comprising a document data file trigger, retrieving, from the resource transfer card, the at least one document data file, encrypting the at least one document data file using a homomorphic encryption protocol, transmitting the at least one homomorphic encrypted document data file, receiving a signal comprising an authentication credential associated with a cardholder of the resource transfer card, recording the authentication credential, and transmitting a decryption key configured to decrypt the at least one homomorphic encrypted document data file.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
4.
Dynamic Event and User Validation Using Reflectance Transformation Imaging
A computing platform may receive, from an initiating user device, an event processing request. The computing platform may generate, using RTI, a first 3D representation of the event processing request. The computing platform may send, to a recipient user device, RTI transformation information indicating transformation actions to be performed, using RTI, to produce a second 3D representation of the event processing request. The computing platform may generate, using the first 3D representation and the second 3D representation, a complete 3D representation. The computing platform identify whether the complete 3D representation is validated. Based on identifying that the complete 3D representation is validated, process the event processing request.
Systems, computer program products, and methods are described herein for an adaptive code packaging interface for customizable single page applications. The present disclosure is configured to define merchant requirements by gathering and analyzing specific information, develop and compile new source code based on these requirements, generate an assembly from the compiled code, and configure deployment parameters tailored to a merchant context. An intelligent deployment tool is used to select Single Page Application (SPA) components from a library, leveraging large language models and prompt engineering. The selected SPA components and custom code are merged into a cohesive deployment package, which is then deployed to application servers. The deployment is validated through tests and performance monitoring to ensure functionality and identify areas for improvement. This system enhances flexibility, efficiency, and adaptability in the deployment of SPAs.
The present disclosure provides a security method, a computing platform, and a system for enhanced online transaction security. The method includes receiving transactional information from a user, and distributing the transactional information over a sensor network of the computing platform. The method also includes generating a decoy transactional block that imitates the transactional information within a blockchain network of the computing platform. The method further includes displaying an association page for the user to enter a verification code and deleting the decoy transactional block from the blockchain network based on determining that the transactional information is authentic.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
7.
MOBILE PHONE PAIRING FOR DYNAMIC SPATIAL ACTIVATION OF COMMUNICATION DEVICE
Apparatus and methods for securing a communication link. The apparatus may include a microprocessor. The apparatus may include a memory cell. The apparatus may include a photovoltaic circuit. The apparatus may include a radio frequency transceiver circuit. The apparatus may include an organic light emitting diode display circuit. The microprocessor may be embedded in an information card. The memory cell may be embedded in the information card. The photovoltaic circuit may be embedded in the information card. The radio frequency transceiver may be embedded in the information card. The organic light emitting diode display may be embedded in the information card. The display circuit may include an array of separately excitable diode fields. The display circuit may include a display controller that is in electronic communication with each of the fields.
G01C 21/20 - Instruments pour effectuer des calculs de navigation
G06K 19/077 - Détails de structure, p. ex. montage de circuits dans le support
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G09G 3/20 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p. ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice
G09G 3/3266 - Détails des circuits de commande pour les électrodes de balayage
Methods and systems for transcribing communications are provided. Methods may include receiving a communication. Methods may include splitting the communication into a plurality of communication segments. Each communication segment may include two or more words. Methods may include transcribing each segment included in the plurality of communication segments, in parallel. The transcribing may include using a transformer neural network to transcribe each segment included in the plurality of communication segments. Methods may include generating a transcription from the transcribing. The transcription may be generated by combining the transcription of each of the communication segments into a combined transcription. Methods may include correcting the combined transcription.
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/30 - Reconnaissance distribuée, p. ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
9.
SYSTEMS AND METHODS FOR STORAGE CACHE PERSONALIZATION AND OBJECT GENERATION USING ADVANCED COMPUTATIONAL MODELS FOR DATA ANALYSIS AND AUTOMATED PROCESSING
Systems, computer program products, and methods are described herein for storage cache personalization and object generation using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive a user interaction from a user account, wherein the user interaction comprises transaction details associated with a transaction; transmit the user interaction to a service layer, wherein the service layer comprises a personalization knowledge model and a bronze storage, wherein the bronze storage comprises unmodified data associated with the user interaction; determine a candidate element, wherein the candidate element is based on a preference of the user; transmit the candidate element to a cache compute engine, wherein the cache compute engine builds a personalized object using the candidate element; and transmit the personalized object to a memory fabric layer, wherein the memory fabric layer is near a user interface of a user device.
G06F 12/128 - Commande de remplacement utilisant des algorithmes de remplacement adaptée aux systèmes de mémoires cache multidimensionnelles, p. ex. associatives d’ensemble, à plusieurs mémoires cache, multi-ensembles ou multi-niveaux
10.
System and method for automated synchronization of data
A system and method for synchronizing data changes. The system is configured to receive a notice from a client device that the client device has updated data and request metadata related to the updated data from the client device that indicates at least a type of data associated with the updated data. The system compares the metadata with first application information and second application information to determine if the first external application or the second external application uses the type of data indicated in the metadata and causes the updated data to be communicated to the first external application but not the second external application when the first external application uses the type of data indicated in the metadata but the second external application does not use the type of data indicated in the metadata.
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
H04L 67/5651 - Conversion ou adaptation du format ou du contenu d'applications en réduisant la quantité ou la taille des données d'application échangées
11.
System and method for authenticating users in a computing system
In response to receiving a voice call from a user, a new voice spectrogram is generated based on the voice of the calling user. A plurality of phonetic indicators are extracted from the new voice spectrogram and compared to phonetic indicators of a plurality of historic voice spectrograms associated with respective users. When a historic voice spectrogram includes one or more of the phonetic indicators extracted from the new voice spectrogram, it is determined that the identity of the calling user is authenticated. On the other hand, when none of the historic voice spectrograms include the one or more of the phonetic indicators extracted from the new voice spectrogram, it is determined that the identity of the calling user is not authenticated.
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p. ex. empreintes digitales, balayages de l’iris ou empreintes vocales
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G10L 17/26 - Reconnaissance de caractéristiques spéciales de voix, p. ex. pour utilisation dans les détecteurs de mensongeReconnaissance des voix d’animaux
12.
SYSTEMS AND METHODS FOR DYNAMICALLY GENERATING NOTIFICATIONS BASED ON CURRENT DATA TRANSMISSIONS OVER A REMOTE ELECTRONIC NETWORK
Systems, computer program products, and methods are described herein for dynamically generating notifications based on current data transmissions over a remote electronic network. The present invention is configured to identify a communication channel comprising a user identifier; train a generative AI engine based on at least one pre-determined guardrail for the communication data in the communication channel, historical user data associated with the user identifier, and at least one issue attribute; collect real time data of the communication channel; apply the real time data to the trained generative AI engine; determine, by the generative AI engine, at least one issue attribute for the communication channel; generate, by the generative AI engine, a dynamic script based on the real time data and the at least one issue attribute; and generate a notification interface component based on the dynamic script.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
Aspects of the disclosure relate to using machine-learning large language models to prevent prompt injection attacks to protect enterprise-managed information and resources. In some embodiments, a computing platform may receive a prompt injection request which is segmented for analysis. The segmented prompt injection request may be analyzed to determine if new learnings are required. If new learnings are required, knowledge graphs are generated to determine new rules for the machine-learning large language model to prevent deceptive prompt injection attacks. The generated new rules may be analyzed to determine the impact on the enterprise based on key performance metrics or organizational health factors before approval and implementation.
G06F 21/52 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données
14.
SYSTEMS AND METHODS FOR DYNAMICALLY CONFIGURING GRAPHICAL USER INTERFACE COMPONENTS BASED ON INTERFACE INTERACTION DATA
Systems, computer program products, and methods are described herein for dynamically configuring graphical user interface components based on interface interaction data. The present invention is configured to identify a user device associated with a user account; identify at least one user access to a platform from the user device; determine, by an emotional artificial intelligence (AI) engine, at least one user platform preference for the user account, wherein the emotional AI engine is pre-trained on historical user platform preference data for the user account; generate, by the emotional AI engine, a user platform interface component based on the at least one user platform preference; and transmit the user platform interface component to the user device, wherein the transmission of the user platform interface component triggers a configuration of the GUI of the user device.
Various aspects of the disclosure relate to identifying and disabling dormant service accounts. An account management system automatically analyzes service account activity records to determine whether each service account defined for an enterprise network is in use. Automated monitoring applications may be used for identifying and authenticating events and/or authentications of service accounts across an enterprise network. When particular service accounts are identified as being potentially dormant, based on an identified date of last use meeting a threshold condition, the associated service accounts are flagged as being dormant. Setting an account as being dormant triggers solicitation of feedback confirming the dormant setting, which causes disablement of the service account. The account management system triggers decommissioning of the dormant service accounts upon expiration of a disablement threshold.
G06F 21/50 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
G06Q 40/02 - Opérations bancaires, p. ex. calcul d'intérêts ou tenue de compte
Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and/or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and/or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable/disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.
Methods and apparatus for using quantum computing processors to execute microdata factories and microdata movers. The methods and apparatus may include receiving a dataset at an entity computing system. The methods and apparatus may include segmenting the dataset into a plurality of data segments using an artificial intelligence (“AI”) model. The methods and apparatus may include leveraging, via quantum entanglement, each of the plurality of data segments at one or more jump point stations. The methods and apparatus may include executing a plurality of microdata movers. Each of the plurality of microdata movers may move each of the plurality of data segments. The methods and apparatus may include executing a plurality of microdata factories. Each of the plurality of microdata factories may sort each of the plurality of data segments.
G05B 19/418 - Commande totale d'usine, c.-à-d. commande centralisée de plusieurs machines, p. ex. commande numérique directe ou distribuée [DNC], systèmes d'ateliers flexibles [FMS], systèmes de fabrication intégrés [IMS], productique [CIM]
G06F 7/08 - Tri, c.-à-d. rangement des supports d'enregistrement dans un ordre de succession numérique ou autre, selon la classification d'au moins certaines informations portées sur les supports
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
18.
SYSTEM AND METHOD FOR ANOMALY DETECTION AND IMAGE-BASED INTERACTION DATA TRANSFER UTILIZING MACHINE LEARNING LEVERAGING SYNTHETIC IMAGE GENERATION
Systems, computer program products, and methods are described herein for anomaly detection and image-based interaction data transfer utilizing machine learning leveraging synthetic image generation. The present disclosure is configured to receive an interaction initiated through an interaction initiation device; generate an interaction image using a set of interaction data associated with the received interaction, wherein the interaction image comprises the set of interaction data associated with the received interaction; distort the interaction image; generate a set of synthetic images associated with the interaction via a machine learning model (MLM); validate the interaction image among the set of synthetic images; and trigger settlement of the interaction within the initiation device upon validation of the interaction image.
A system is provided for generating artificial intelligence based visualizations of computing device security and stability. In particular, the system may aggregate various types of data and metrics related to the operational performance, security, and stability of the computing devices and applications within an entity's computing environments. Based on the aggregated data, the system may use an artificial intelligence engine to determine whether a particular area, network, application, or device may be vulnerable. Based on analyzing the data, the system may generate one or more visualizations of the data that reflect the current state of the entity's computing environment as a whole. The system may further be configured to transmit notifications to one or more relevant users associated with the applications or devices subject to the vulnerabilities.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/56 - Détection ou gestion de programmes malveillants, p. ex. dispositions anti-virus
In response to detecting a request from a first user to perform a data interaction, a first hash key value is generated based at least in part upon a first set of data values included in the request. The first hash key value is compared to a verified second hash key value associated with the first user. In response to detecting that the first hash key value does not match with the verified second hash key value, it is determined that the digital identity of the first user is not authenticated, an alert is generated, and processing of the requested data interaction is stopped.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
In response to detecting a request from a first user to perform a data interaction, a set of parameters associated with processing of the requested data interaction is monitored. In response to determining that an anomalous activity has occurred in relation to the processing, a response associated with the processing is obtained and software code included in the response is obfuscated to generated obfuscated code. The software code is replaced with the obfuscated code in the response, and the response including the obfuscated code is transmitted to a user device that initiated the request.
Apparatus for implementing a quantum communication system between an entity and a user includes collecting user-relevant historical data and current behavioral data with an artificial intelligence and/or machine learning module. One or more quantum computing processors may analyze and shrink the data into reduced datasets. One or more quantum algorithms may be used to shrink the data. The one or more quantum computing processors may create a plurality of contact points associated with the user that are based on the reduced datasets. A standard script associated with the interaction may be adjusted using the contact points. The adjusted script may be presented to an agent associated with the entity to conduct the interaction.
Embodiments of the present invention provide a system for generating digital representation of resources to perform real-time comparison and assessment of resources. The system is configured for receiving a request to view at least one resource of a plurality of resources from a user in a mixed reality environment, via a user device, determining that a digital representation of the at least one resource of the plurality of resources does not exist in a data repository, instantaneously generating the digital representation of the at least one resource of the plurality of resources based on communicating with external systems, instantaneously generating an immersive representation of the at least one resource of the plurality of resources based on the generated digital representation, and displaying at least a part of the immersive representation of the at least one resource of the plurality of resources in the mixed reality environment of the user.
G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
24.
INTELLIGENT SYSTEM AND METHOD TO DERIVE A NORMALIZED CONSENT PROTOCOL FOR HETEROGENEOUS DISTRIBUTED LEDGER LEVERAGING NEURO-SYMBOLIC ARTIFICIAL INTELLIGENCE (AI)
A system and method may generate a normalized protocol model that leverages heterogeneous distributed ledger technology and is interoperable across different blockchain networks that may initially use different network protocols. The model may be generated by leveraging neuro-symbolic artificial intelligence (AI). The model that is generated may be based on the different network protocols that are in use at the different blockchain networks. The model may be adopted by the blockchain networks upon the blockchain networks providing unified consent to its adoption. The model may be required to be implemented by each of the different blockchain networks. The consensus to adopt the model may be recorded in one or more smart contracts. Copies of the smart contracts may be stored at the blockchain networks. The normalized protocol model may allow electronic transaction, data exchanges, and communications to be performed across blockchain networks and recorded in a heterogeneous distributed ledger.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06F 21/10 - Protection de programmes ou contenus distribués, p. ex. vente ou concession de licence de matériel soumis à droit de reproduction
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
25.
REDUCING APPLICATION CARBON FOOTPRINTS USING PREDICTIVE LOAD BALANCING AND ADAPTIVE PROCESS SCALING
Aspects related to reducing application carbon footprints using predictive load balancing and adaptive process scaling are provided. An adaptive scaling platform may train a delegation model to output event pools based on input of event processing traffic information. The platform may receive event processing traffic information. The platform may generate an event pool using the delegation model. The event pool may comprise tasks required to fulfill event processing requests corresponding to the event processing traffic information and indicators of applications corresponding to the plurality of tasks. The platform may receive event processing information from a server. The platform may cause, based on the event processing information, an application to identify thread requirements. The computing platform may allocate resources based on the thread requirements. The computing platform may delegate tasks to the threads based on the allocating. The platform may update the delegation model based on monitoring the threads.
Systems, computer program products, and methods are described herein for routing data transmissions using machine learning models and enriching data using artificial intelligence. The present disclosure is configured to: receive a dataset comprising a set of elements; rank the received dataset among a plurality of datasets via a machine learning model (MLM), wherein ranking the received dataset determines priority of the received dataset within the plurality; generate a summary of the set of elements within the dataset via an artificial intelligence engine; identify a team via the MLM, based on rank and the summary of the set of elements of the dataset, to process the received dataset; and transmit the dataset to the team identified by the MLM.
Systems, computer program products, and methods are described herein for improving network and data security by automatically preventing rogue database queries. The present disclosure is configured to identify a query request, wherein the query request comprises query request metadata; apply the query request to a generative adversarial network (GAN) model, wherein the GAN model is protected by a security gateway; generate, by the GAN model, a result metadata based on the query request, wherein the GAN model is trained on a database schema; and determine, based on a comparison of the query request metadata and the result metadata, whether to allow the query request by the security gateway.
A comprehensive and centralized system for managing and tracking communications being delivered through both digital communications channels and physical communication channels. A centralized computing hub receives communication requests from originating systems of record or via user input. In response to receiving a communication request, content is generated or otherwise obtained and quality assurance checks are performed to assure that the content meets the requirements of the originating system of record and is applicable to the intended communication recipient. Once the quality checks have been performed and the content is deemed verified, delivery of the communications is orchestrated in accordance with the chosen communication channel. The timeliness of the communications is tracked throughout the system and alerts are generated in response to the timeliness exceeding thresholds. Thresholds are intelligently determined on a continuous basis using rolling averages of previous communications that result in predictions of future communication averages.
Embodiments of the present invention provide a system for identifying and blocking synthetic media based misappropriation attempts associated with electronic communications. The system is configured for identifying initiation of an authentication request from a user device of a user, monitoring and recording user characteristics via the user device, capturing user environment data of the user, via the user device, analyzing the user characteristics and the user environment data of the user, via an artificial intelligence engine, determining, via the artificial intelligence engine, if the authentication request is a misappropriation attempt based on at least one of the user characteristics and the user environment data, and performing an action comprising authenticating the user based on determining that the authentication request is not a misappropriation attempt or denying authentication of the user based on determining that the authentication request is a misappropriation attempt.
Arrangements for providing semi-dynamic vulnerability detection are provided. In some aspects, a computing platform may receive work flow data from one or more systems and may analyze the work flow data using a GAN. The GAN may output a potential vulnerability identified in the data, and a category of the potential vulnerability. Based on the potential vulnerability and the category, the computing platform may determine a severity of the potential vulnerability. An ANN-SNN converter may be executed to output a knowledge graph including a plurality of nodes forming a mitigation action plan for the potential vulnerability. The computing platform may generate a digital twin of the knowledge graph and may then reconcile the digital twin by back tracking through each node to validate each node of the digital twin. Based on the digital twin being reconciled, the generated mitigation action plan may be transmitted to a computing system for execution.
Various aspects of the disclosure relate to utilizing recurrent neural network (RNN) technologies to facilitate simulation of brain inspired data storage patterns in analog storage media via neuromorphic computing. An RNN-based analog cache system incorporates a self-adjusting mechanism that constantly evaluates the relevance and/or usage patterns of stored data. When data becomes obsolete and/or is less frequently accessed, the neural connections of the RNN-based analog cache system are dynamically readjusted to prioritize more relevant information, thus optimizing cache utilization. The RNN-based analog cache system captures one or more temporal relationships between different stored data elements to automatically learn and leverage temporal dependencies, to predict future data access patterns from users and/or applications accessing data stored within the RNN-based analog cache
G06N 3/0442 - Réseaux récurrents, p. ex. réseaux de Hopfield caractérisés par la présence de mémoire ou de portes, p. ex. mémoire longue à court terme [LSTM] ou unités récurrentes à porte [GRU]
Systems, computer program products, and methods are described herein for automatically building dynamic queries for identifying data in unstructured datasets. The present disclosure is configured to receive a plurality of query templates associated with an alert type(s); identify an unstructured database note(s) based on a user identifier; apply the unstructured database note(s) and the plurality of query templates to an unstructured notes search engine; generate, by the unstructured notes search engine, at least one raw score for the at least one unstructured database note and for each alert type(s); transform, by the unstructured notes search engine, the at least one raw score to a relevancy score using a quantile transformation; and determine a highest relevancy score for each of the at least one unstructured database note for the user identifier.
Verification of peer-to-peer network transmission occurs implementing AI to determine a match between the purpose/intent of the peer-to-peer network transmission as defined by the sending entity/peer and the purpose/intent of the peer-to-peer network transmission as defined by the recipient entity/peer. The sending peer initiates communication of a peer-to-peer network transmission, which identifies the recipient peer and purpose of the transmission. The peer-to-peer network transmission is captured and held in a transmission pending queue. A push notification is communicated to the recipient entity/peer identified in the transmission, which requests input of their perceived purpose/intent of the transmission. Once the recipient entity/peer identified in the transmission responds with their purpose of the transmission, an AI model trained to determined matches between inputted purposes/intents is executed. Once the AI model determines a purpose/intent match, the transmission is released for the transmission pending queue, so that further communication and/or processing of the transmission occurs.
H04L 67/1074 - Réseaux de pairs [P2P] pour la prise en charge des mécanismes de transmission de blocs de données
H04L 67/1087 - Réseaux de pairs [P2P] en utilisant les aspects inter-fonctionnels d’établissement de réseau
34.
CRON-based routing machines and processes to schedule and execute java code excerpts across fault-tolerant load-balanced distributed servers running JVM namespaces
A routing process schedules and executes Java code excerpts across backend servers. A route table contains routes to be executed in JVM namespaces on servers and identifies for each route a Jar file containing applicable classes and methods to be executed at a CRON time. During execution, methods are retrieved from each applicable class and are executed to extract data from backend devices. The servers transform the extracted data into frontend data and load it onto frontend storage devices. Only the classes and methods in the Jar file for a route need be executed. Complete Java programs need not be run.
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
35.
Leveraging quantum entanglement for replicating data in multiple locations and twin tagging the data
The method may include secure data transfer to meet a compliance requirement by using quantum computing over a quantum network. A quantum computer may establish quantum entanglement between qubits, save a data set to a first set of qubits, and teleport correlated quantum states of the data set to a second set of qubits situated at a different location. Quantum error correction may lengthen the storage time of the data set on the first set of qubits before the quantum states of the first set of qubits expire due to decoherence. The quantum computer may tag the quantum states of the data set on each set of qubits to aid in identification of the locations of each set of qubits. Teleporting the data set between locations on a quantum network may lead to less energy expenditure and reduced network travel compared to transporting the data set over a binary network.
Intelligently determination of intent of a resource provider when attempting to delete a resource event device, specifically, the resource event credentials associated with the resource event device, from a network location. Intent is determined by implementing Artificial Intelligence (AI) to analyze the resource provider's historical data to determine a probable/possible intent and, in response, queries are presented to the resource provider that attempt to confirm the probable/possible intent as the actual intent. In response to determining the intent, the invention is configured to perform one or more actions that are based on the determined intent.
Systems, computer program products, and methods are described herein for predictive generation of electronic query data. The present invention is configured to electronically receive a query string associated with an administrative body, wherein the query string corresponds to a response field, and wherein the response field is configured to receive a response string; retrieve, from a database associated with an entity, information associated with the administrative body; determine an administrative record associated with the administrative body, wherein the administrative record comprises one or more prior response strings; generate one or more customized autofill options for the response string based on at least the information associated with the administrative body and the administrative record associated with the administrative body; and transmit control signals configured to cause the endpoint device of the user to display, on a graphical user interface, the one or more customized autofill options to the user.
Apparatus, methods and systems for contextual prediction processing is provided. Methods may include receiving a conversation from an entity. The conversation may include current utterance, previous utterances and details. Methods may include using an action-topic ontology to build, using data retrieved from the current utterance, a conversation frame that corresponds to the current utterance. Methods may include merging the conversation frame with data, retrieved from the previous utterances and the details, to generate a target conversation frame. Methods may include validating the target conversation frame to prevent looping over historic data in the event that the current utterance fails to add relevant information. Methods may include generating an enhanced contextual utterance based on algorithms and the target conversation frame. The enhanced contextual utterance may be used to understand the current utterance in a context of the conversation. Methods may include returning the enhanced contextual utterance to the entity.
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive a request for transaction from a transaction processing card via a card reader of a transaction processing device. The computing platform may dynamically generate a validation code. The computing platform may transmit the validation code to the transaction processing card. In some examples, the computing platform may receive, from the transaction processing card, an encrypted version of the validation code. The code may be encrypted by the transaction processing card using a key associated with the transaction processing card. The computing platform may attempt to decrypt the encrypted code with a key associated with the transaction processing device. If the decryption is successful, the transaction may continue. If decryption is not successful, the transaction may be denied and a notification indicating that the transaction processing card is compromised may be generated and transmitted to a computing device.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
40.
Automated Teller Machine (ATM) Exception Identification and Analysis
Arrangements for identifying, analyzing, and remediating automated teller machine (ATM) exceptions are provided. A computing platform may configure an exception mapping table to match an exception code to a corresponding exception type. The computing platform may receive exception codes associated with one or more automated teller machines (ATMs). The computing platform may map the exception codes to corresponding exception types. The computing platform may compile exception ranking information into a ranked list. The computing platform may identify a subset of ATMs to take action on. The computing platform may identify actions to remediate issues related to the exception codes. The computing platform may automatically execute the identified actions.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
41.
SYSTEM AND METHOD FOR CONTROLLING AND SECURING NETWORK CONNECTIVITY USING SWARM INTELLIGENCE
Embodiments of the present invention provide a system for controlling and securing network connectivity using swarm intelligence. The system is configured for determining initiation of a network connection from a user device of a user with a network device, performing encryption of data packets associated with the initiation of the network connection before transmitting the data packets to the network device, transmitting the encrypted data packets associated with the initiation of the network connection to the network device, extracting one or more identifiers associated with the network device, determining if the network device is secure, via an artificial swarm intelligence engine, and performing an action comprising establishing the network connection based on determining that the network device is secure to connect or denying the network connection based on determining that the network device is not secure to connect.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
42.
System and Method for Generating User Specific Interactive Voice Responses Based on User Speech and Voice Characteristics
A system includes a memory configured to store user profiles associated with a plurality of users and an interactive voice response (IVR) system configured to service calls. The system includes processors configured to receive a call from a first user, generate a first voice interaction configured to prompt the first user to perform an utterance of a second voice interaction, and detect the utterance of the second voice interaction. The processors are configured to execute a first machine-learning model trained to identify speech and voice characteristics of the first user and to generate a third voice interaction based on the identified speech and voice characteristics. In response to identifying an intent and one or more named entities of the request, the processors are configured to initiate the execution of one or more interactions with the first user profile in accordance with the identified intent and one or more named entities.
H04M 3/493 - Services d'information interactifs, p. ex. renseignements sur l'annuaire téléphonique
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/183 - Classement ou recherche de la parole utilisant une modélisation du langage naturel selon les contextes, p. ex. modèles de langage
43.
System and Method for Generative Design Based Real-Time Restricted Sub Application Setup with Non-Production Data Architectural Flow Determination with Enterprise Scoped Large Language Injection Model
Systems and processes enhance cybersecurity by dynamically generating a decoy sub-application that operates parallel to the primary application using generative design and a large language model. The core feature involves real-time anomaly detection within application traffic, utilizing AI to assess threats and orchestrate appropriate responses. Upon identifying potential security threats, the system employs generative design principles to architect a restricted-functionality sub-application, deploying it instantly to engage and analyze the attack vectors without compromising sensitive production data. The sub-application is isolated through software-defined networking, ensuring that its operations do not affect the primary application's functionality. Additionally, sophisticated traffic redirection mechanisms are employed to divert suspicious traffic from the primary to the decoy application, thereby protecting the integrity while allowing detailed threat analysis. This dual-capability system not only safeguards against disruptions but also enhances adaptive security measures through continuous learning and system adjustments.
Apparatus and methods for proactively and preemptively communicating with a user interacting with a software application are provided. The apparatus and methods may include an artificial intelligence/machine learning communication engine monitoring and tracking a user's interactions. The apparatus and methods may include the communication engine determining if the user requires further training, if the interaction is fraudulent, and pre-empting requests for information the user may commence. The apparatus and methods may include the communication engine creating and displaying training materials for the user to complete, revoking access if fraud is present, and proactively providing information before the user requests the information.
A computer implemented system and method are disclosed involving technological advancements in the processing of electronic transaction processing results. The system may comprise a computer apparatus implementing a checking account system, a savings account system, a merchant account and investment account on a funds management system, and one or more computer systems and mobile devices including a communication interface, processor, memory storing computer-executable instructions, and savings modules. Reward amounts may be calculated based on various techniques.
G06Q 40/06 - Gestion de biensPlanification ou analyse financières
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive an indication that a transaction has been initiated at a transaction processing device. The platform may receive, from one or more sensors arranged on the transaction processing card, magnetic field data associated with a magnetic field detected when the transaction processing card is inserted into the card reader. The platform may execute a machine learning model using, as inputs, the magnetic field data, to output any detected discrepancies between the current magnetic field data and expected magnetic field data. If a discrepancy is detected, the computing platform may identify that a shimming device is present at the card reader of the transaction processing device. A notification indicating that the shimming device is present may be generated and transmitted to, for instance, the transaction processing card.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
48.
Unauthorized Activity Detection at Automated Teller Machine
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive an indication that a transaction has been initiated at a transaction processing device. The computing platform may receive, from one or more sensors arranged on the transaction processing card, capacitance data associated with a capacitance detected when the transaction processing card is inserted into the card reader. The computing platform may execute a machine learning model using, as inputs, the capacitance data, to output any detected discrepancies between the current capacitance data and expected capacitance data. If a discrepancy is detected, the computing platform may identify that a skimming device is present at the card reader of the transaction processing device. A notification indicating that the skimming device is present may be generated and transmitted to, for instance, the transaction processing card and may cause a light emitting diode on the transaction processing card to illuminate.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
49.
GRAPHICS PROCESSING UNIT (GPU) OPTIMIZATION USING HASH TABLES
A computing platform may receive a GPU processing request for processing by a GPU system. The computing platform may identify an operation requested by the GPU processing request. The computing platform may identify whether or not the operation is stored in a hash table. Based on identifying that the operation is not stored in the hash table, the computing platform may identify whether an approximate match of the operation is stored in the hash table. Based on identifying that the approximate match is stored in the hash table, the computing platform may identify a first key stored, in the hash table, along with the approximate match. The computing platform may identify, using the first key, a location of a solution to the approximate match of the operation. The computing platform may obtain, from the location, the solution to the approximate match of the operation, and may apply the solution.
Systems, apparatus and methods for creating and enforcing real-time counter-malicious rules are provided. Methods may include monitoring, using a quantum processing unit, interactions on a network. Methods may include identifying, using the quantum processing unit, one or more fraudulent activities included in the interactions. Methods may include amalgamating, using the quantum processing unit, the fraudulent activities. Methods may include rebuilding, using the quantum processing unit, one or more fraudster rules used by one or more entities executing the one or more fraudulent activities. Methods may include building, using the quantum processing unit, one or more elastic counteractive rules, said elastic counteractive rules counteracting the one or more fraudster rules. Methods may include executing, using the quantum processing unit, the elastic counteractive rules within the network. Methods may also include halting, using the quantum processing unit, the one or more fraudulent activities within the network using the elastic counteractive rules.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
51.
SYSTEM AND METHOD FOR REAL-TIME MONITORING AND REMEDIATION OF NETWORK INTRUSION USING AN INTELLIGENT APPLICATION PROGRAMMING INTERFACE
A system is provided for real-time monitoring and remediation of network intrusion using an intelligent application programming interface. In particular, the system may monitor and track, in real time, the various computing devices within a distributed networked system. The system may use one or more trained artificial intelligence models to analyze incoming network requests and detect anomalies within the body of network requests, and based on the analysis, implementing one or more countermeasures (e.g., request throttling, rate limiting, allocation of additional computing resources, and/or the like) in response. In some embodiments, the one or more AI models may be configured to generate intrusion mitigation and/or remediation plans in response to any detected anomalies. The output of the AI models may then be wrapped with additional data that may enhance the anomaly detection process.
The present invention relates to systems and methods for proactive real-time anomaly detection in cross-environment RPC (Remote Procedure Call) communications within computing systems. Utilizing an Intelligent GraphRPC Method, this invention integrates advanced graph analysis techniques to enhance fault detection and workflow management. The method features a dual-graph approach, employing both real-time and aggregated dependency graphs, which allows for continuous monitoring and analysis of RPC interactions to detect and prevent unauthorized or misconfigured RPC calls between staging and production environments. An ingestion pipeline further supports the system by aggregating and archiving call graph data, providing beneficial insights into service dependencies and potential security risks. This proactive anomaly detection system is designed to seamlessly integrate into existing monitoring and alerting frameworks, providing a robust solution to safeguard data integrity and operational stability, thereby minimizing losses and reputational damage due to data breaches and system disruptions.
A system includes a memory configured to store user profiles associated with a plurality of users and an interactive voice response (IVR) system configured to service calls. The system includes processors configured to receive a call from a first user, generate a first voice interaction configured to prompt the first user to perform an utterance of a second voice interaction, and detect the utterance of the second voice interaction. The processors are configured to detect the utterance of the second voice interaction, execute a machine-learning model trained to identify speech and voice characteristics of the first user and to generate a third voice interaction based on the identified speech and voice characteristics, dynamically adjust IVR response features associated with the third voice interaction based on the identified speech and voice characteristics, and output the third voice interaction in accordance with the dynamically adjusted one or more IVR response features.
Arrangements for detecting and resolving automated teller machine (ATM) anomalies are provided. A computing platform may receive information related to one or more automated teller machines (ATMs) that may include one or more anomalies. The computing platform may preprocess the information to remove one or more false positives from the information. The computing platform may apply anomaly detection logic to the preprocessed information to identify one or more anomalies. The computing platform may output one or more anomaly codes that correspond to the identified one or more anomalies. The computing platform may identify and subsequently execute one or more actions to resolve the one or more anomalies.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
55.
NATURAL LANGUAGE GENERATION SYSTEM FOR AUTOMATED TRANSLATION OF DIGITAL MULTIMEDIA
Systems, computer program products, and methods are described herein for automated translation of digital multimedia. The present disclosure is configured to receive, from a user input device, a search request; determine the response for the search query in a first natural language, wherein the response comprises digital multimedia; reconfigure the response for display on the user input device in the preferred natural language, wherein reconfiguring further comprises: determining an intermediate natural language based on a lexical similarity with the preferred natural language; translating, using a first natural language translation subsystem, the response from the first natural language to the intermediate language; and translating, using a second natural language translation subsystem, the response from the intermediate language to the preferred natural language; and display the reconfigured response on the user input device in the preferred natural language.
G06F 40/40 - Traitement ou traduction du langage naturel
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
H04N 21/43 - Traitement de contenu ou données additionnelles, p. ex. démultiplexage de données additionnelles d'un flux vidéo numériqueOpérations élémentaires de client, p. ex. surveillance du réseau domestique ou synchronisation de l'horloge du décodeurIntergiciel de client
H04N 21/439 - Traitement de flux audio élémentaires
56.
COLLABORATIVE VERIFIED USER PLATFORM USING DISTRIBUTED LEDGER TECHNOLOGY
Aspects of the disclosure relate to a collaborative verified user platform using distributed ledger technology. A collaborative verified user platform may identify changes to user information stored at a distributed ledger. The platform may retrieve changes from a remote database. The platform may update the distributed ledger based on the changes. The platform may receive, from a second user device, a request to access the user information. The platform may establish a secure channel. The platform may process one or more secure requests associated with a venture corresponding to both the first user device and the second user device. The platform may detect a permission violation. The platform may initiate security actions based on the permission violation. The platform may receive an updated cyber contract corresponding to the user information. The platform may update permissions based on the updated cyber contract.
Apparatus and methods for quantum-computing based file remediation are provided. A quantum file remediation program on a computer system with a standard processor and an “N”-qubit processor may receive a network file. When a file attribute score determined on the standard processor deviates by more than a predetermined amount from a baseline score, the program may initialize a quantum circuit. A deep learning framework using a quantum generative adversarial network (QGAN) may run on the quantum circuit and generate a remediated file. When the QGAN session ends, the quantum circuit may be collapsed and the original network file may be replaced by the remediated file.
Systems, computer program products, and methods are described herein for migrating application functionality using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive, via a learning agent, a transaction incident associated with a source application in a transaction, wherein the transaction comprises one or more applications, and wherein the learning agent comprises learning the applications' functionality; determine, using a real time incident listener, a scope of the transaction incident; access an application inventory to determine a target application, wherein the application inventory comprises a database of applications, and wherein the database of applications is associated with an entity that is associated with the system; generate, using a script generator, a script, wherein the script comprises a source function associated with the source application; deploy the script to the target application; and monitor the target application with a federated learning module.
Systems, computer program products, and methods are described herein for automatically generating and implementing password rotations using artificial intelligence. The present invention is configured to identify at least one password rule associated with at least one application; train a machine learning model by applying the at least one password rule; determine, by the trained machine learning model, whether a password rotation requirement is present for the at least one application; generate, by an artificial intelligence (AI) bot, an updated password for the at least one application in an instance where the password rotation requirement is present; validate the updated password for the at least one application; and automatically update, based on the validation of the updated password, the at least one application with the updated password.
A method is provided that includes receiving a request to perform an interaction that includes user data and device data. The method includes splitting the user data into one or more logical data components. The method includes comparing the one or more logical data components to one or more predetermined validation thresholds. The method includes determining whether the one or more logical data components satisfy the one or more predetermined validation thresholds. In response to determining that the one or more logical data components satisfy the one or more predetermined validation thresholds, the method includes obfuscating the one or more logical data components to generate one or more unique identifiers, and obfuscating the device data to generate a unique device identifier. The method includes generating an authentication response configured to authorize the external entity server to perform the interaction that includes the unique identifiers and unique device identifier.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Systems, computer program products, and methods are described herein for network event data streaming and processing via modular network event data architecture. The present disclosure includes receiving a plurality of network event data in real-time, determining a feature of at least one network event data, labeling the at least one network event data with a label corresponding with the feature, retrieving a preconfigured routing path, routing, from the input module to a first processing module, the at least one network event data, wherein the first processing module is reusable for other preconfigured routing paths, and transforming the network event data in accordance with the predetermined rule.
Systems, computer program products, and methods are described herein for authenticating digital IDs over an electronic network using dual authentication in a distributed network. The present disclosure is configured to identify a primary communication channel from a user device; generate an authentication prompt for the primary communication channel; transmit the authentication prompt to the user device; identify, based on the authentication prompt, an authentication credential from a secondary communication channel associated with the user device; and authenticate the authentication credential based on a digital identifier associated with the user device.
In response to detecting that a first error associated with processing a first job by a first software application has occurred, a jobs manager obtains a first error message associated with the first error and determines whether the first error message is one of a plurality of known error messages associated with the first software application. In response to determining that the first error message is one of the known error messages associated with the first software application, the jobs manager obtains a first known recovery plan associated with the first error message and performs one or more recovery steps associated with the first known recovery plan to resolve the first error associated with the first software application.
In response to determining that a first error message associated with a first software application is not a known error message associated with the first software application, a jobs manager determines a second software application of a plurality of software applications that is associated with a same or similar known error message as the first error message and obtains a first known recovery plan associated with the same or similar known error message. The jobs manager then generates a customized recovery plan for the first software application based at least in part upon the first known recovery plan, wherein the customized recovery plan comprises one or more customized recovery steps associated with resolving the first error. The jobs manager performs one or more of the customized recovery steps associated with the customized recovery plan to resolve the first error associated with the first software application.
After generating a first customized recovery plan to resolve a first error associated with a first error message generated by a first software application, a jobs manager obtains identities of an input system, an output system or a combination thereof associated with the first software application. In response to determining that a second software application is associated with the same or similar input system, the same or similar output system, or the combination thereof as the first software application, the jobs manager determines that the first error associated with the first software application is predicted to occur relating to the second software application. Thereafter, the jobs manager generates a second customized recovery plan for the second software application based at least in part upon the first customized recovery plan generated for the first software application.
Systems, computer program products, and methods are described herein for verifying devices using advanced computational models for data analysis and automated processing. The present disclosure is configured to initiate a resource transaction, wherein the resource transaction is initiated via a sender device, and wherein the resource transaction comprises transferring a resource from a sender resource container to a receiver resource container via the sender device and a receiver device; generate a primary contract, wherein the primary contract comprises encrypting a data packet associated with the resource transaction and wherein the data packet comprises resource transaction details; generate a secondary contract, wherein the secondary contract comprises verifying the receiver device; and execute the resource transaction, wherein executing the resource transaction comprises providing the data packet to a sender entity, and wherein the sender entity is associated with the sender resource container.
A method is provided that includes receiving an interaction request that comprises interaction data. The method includes processing the interaction data using software applications in an interaction validation pathway, receiving a content error associated with processing the interaction data in the interaction validation pathway, and determining whether a pre-determined content correction is configured to correct the content error. If not, the method includes generating a content correction using a machine learning model, generating a simulated environment for processing the interaction data with a simulated interaction validation pathway, applying the content correction to the first content error in the simulated environment, and determining whether the content correction corrects the content error in the simulated environment. If so, the method includes generating modified interaction data by applying the first content correction to the first content error, and processing the modified interaction data using the interaction validation pathway.
A method for dynamically generating a user interface (“UI”), the UI for use with a source application is provided. The method may include tagging each field within the source application to one or more priority levels. The method may include identifying a user accessing the source application. The method may include identifying a user priority level and a plurality of historic pattern behaviors of the user. The method may include generating the UI based on the user priority level and the plurality of historic pattern behaviors. The method may include dynamically monitoring the user's usage. The method may adjust the UI based on the usage. The generating the UI may include adding each field tagged to the user priority level and adding each field associated with the historic pattern behaviors to the UI. The adjusting may include adding, removing and changing at least one field generated on the UI.
Methods for banking at an automated teller machine (ATM) using a mobile device. The ATM may automatically detect the presence of the mobile device in a vicinity of the ATM and initiate contact with the mobile device, or a mobile device may initiate contact with the ATM. After verifying user permission to access the ATM, the mobile device may be enabled to provide user access to one or more of the banking services available at the ATM using the mobile device and to view banking-related information on the mobile device. A mobile application on the mobile device may be used to access the ATM using the mobile device. While a mobile device is accessing the ATM, a screen on the ATM may become inactive for banking services and the option to select banking services directly at the ATM may be disabled.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Apparatus and methods for an artificial intelligence implemented termination by an auditor artificial intelligence (“aAI”) of a malicious artificial intelligence (“mAI”) are provided. The aAI may detect a mAI on a network and determine which data the mAI can access on the network. The aAI may then degrade all or part of the data in various ways to prevent the mAI from producing valid content based on the data. The aAI may also create code and inject the code into the mAI to degrade the mAI's operations. As the mAI may rely on valid data to produce valid output, degrading the data may degrade the mAI.
Embodiments of the invention are directed to systems, methods, and computer program products for proactive resiliency, redundancy and security remediation across a network based on dynamic analysis of technology applications. The invention involves determining whether an entity communication network comprises at least one first redundant technology application associated with the first technology application such that the at least one first redundant technology application renders at least one processing activity of the first technology application resilient. Here, the invention involves constructing network vulnerability components associated with a first data flow comprising an open vulnerability component, an unauthorized technology component, and an open security component. The invention may determine a prognostic failure associated with the first data flow based on determining that the entity communication network does not comprise at least one first redundant technology application associated with the first technology application.
H04L 41/0654 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/16 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel
A system is provided for implementing time-restricted access control to electronic digital resources. In some embodiments, the custom set of executable code used to generate the digital resource may provide granular control over access restrictions for accessing, viewing, and/or transferring the digital resource. Such access restrictions may include time duration restrictions, access frequency restrictions, data quality restrictions, and/or the like. In this way, the system may limit access to the digital resource in a secure manner.
Systems, computer program products, and methods are described herein for implementing real time protocol modifications for address resolutions protocols in a network environment. The present disclosure is configured to identify an address resolution protocol (ARP) cache table comprising an internet protocol (IP) address and a media access control (MAC) address for a communication mapping(s); determine a firewall property(ies) of the ARP cache table for the communication mapping(s); compare the firewall property(ies) to at least one normal firewall property and determine whether the firewall property(ies) is anomalous compared to the normal firewall property(ies); automatically execute a smart contract, wherein the smart contract comprises an authorization protocol(s) for the ARP cache table and an execution of a homomorphic encryption for the ARP cache table; and protect the ARP cache table based on the execution of the smart contract with the authorization protocol(s) and the homomorphic encryption.
A system for improving performance of a website is disclosed. The system detects web components associated with the website and determines conditional metrics. The conditional metrics indicate a range of conditions under which the performance of the website is evaluated. The system generates a set of test case scripts to emulate various user interactions with the website under various conditions according to one or more conditional metrics. The system executes a first test case script to emulate a first user interaction with a first web element under a first condition. The system determines that a result of the first test case script does not correspond to an expected output. In response, the system performs a corrective action, including updating a code portion associated with the first web element in the source code of the website to a code portion that is configured to provide the expected output.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
75.
Multi-Function Device Having Dynamic Toggle Capabilities
Arrangements for providing multi-functionality device control functions are provided. In some aspects, a request for transaction may be received by a computing platform. The request may include transaction details including selection of a mode of processing, received from a payment device. The computing platform may determine whether the selected mode of payment is crypto currency. If so, the transaction details may be transmitted to a peer-to-peer network for validation of the transaction. If the transaction is validated, a new block, corresponding to the validated transaction, may be generated and added to a blockchain and the transaction may be processed. In some examples, additional details of the transaction may be received and the additional details and the transaction details may be input to a machine learning model. Upon execution of the model, an environmental impact score associated with the transaction and a recommendation may be determined and transmitted to the user.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
76.
System and method to dynamically analyze representative application data
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to generate a representative application in a simulation environment based at least in part upon an application data. The processor is further configured to execute the machine learning algorithm to perform one or more obfuscation operations configured to at least partially replace application information of the application data with simulation information of a specific data type; purge the application information from the simulation environment; simulate multiple application operations by the representative application using the simulation information; determine whether the simulated application responses comprise an output that is different from any of those in expected application responses in response to monitoring the simulated application responses during simulation of the application operations; and determine a modification suggestion to multiple application configuration parameters of the application configured to inhibit the output in response to determining the output.
Methods, systems and apparatus for detecting, monitoring and forecasting for compromised electronic communications in an electronic communication system. Methods may include isolating, from a historical database, electronic communications associated with a plurality of senders into individual data capsules. Methods may include generating and storing a predictive analytic profile for each sender based on a communication style identified for each sender. Methods may include filtering out compromised electronic communications using a dynamic quantum filter, the dynamic quantum filter including a dynamic condition set. Filtering may include inserting a quantum signature into each incoming electronic communication. Methods may include retrieving the predictive analytic profile associated with the sender identified for each incoming electronic communication. Methods may include assigning condition values to each electronic communication based on comparing each electronic communication to a corresponding predictive analytic profile. Methods may include determining whether the assigned condition values conform with the dynamic condition set.
Systems and methods for a system architecture for supporting bifurcated data transmission are provided. The system architecture may include a point-of-sale (“POS”) device. The system architecture may include a central server. The POS device may break up a transaction request received from a requestor into micro-data. Each micro-data may include a tiny portion of the transaction request and a header. The header may identify the transaction request and a number that identifies a location of the micro-data within the transaction request. The POS device may send the micro-data to a quantum processor for arranging the micro-data in a queue in a random order. The POS device may also compile a confirmatory data packet including data identifying the point-of-sale device and a total number of the micro-data. The confirmatory data packet and the micro-data, in the random order, may be transmitted to the central server.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
79.
Dynamic Feature Optimization Leveraging Quantum Simulation for Fake Account Detection
Robust systems and methods are disclosed for fake account detection on digital platforms, integrating provenance analysis to scrutinize data origins, ownership, and history, thereby unveiling potential sources of fraudulent activities. They leverage dynamic feature generation, using advanced algorithms to assess user behaviors and interactions, ensuring the model stays attuned to the evolving landscape of cyber threats. Incorporating Quantum-assisted optimization, the method employs Quantum algorithms to expedite feature selection, enhancing detection efficiency. Quantum simulation further refines this process, creating sophisticated verification patterns and analytical techniques to distinguish genuine from fake accounts with higher accuracy. A comprehensive analysis amalgamates provenance data, telemetry, and dynamic features, forming a holistic detection approach. This system optimizes features through Quantum simulation, tailoring them to specific business environments, and deploys them via AI-ML DevOps, streamlining orchestration across various operational settings.
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
80.
VIRTUAL REALITY HEADSET AND ARTIFICIAL INTELLIGENCE VIRTUAL ASSISTANT INTEGRATION FOR ADDRESSING A LANGUAGE BARRIER WITH A CUSTOMER
A method for improving service to a user encountering a language barrier. The user may encounter a language barrier when speaking to an agent or using a computer application of an organization. The user may use a VR headset to translate its request for assistance into a language used at the organization and transmit the translated request to an AI virtual assistant. The AI virtual assistant may confirm its understanding of the user's request, determine an agent in a team in the organization that can assist the user, and transfer the user to that agent. The user and the agent may each speak in a language in which they are proficient, even though the other is not proficient in that language, to resolve the user's request. An API may integrate the AI virtual assistant with the VR headset to facilitate real-time communication between the user and the agent.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G06Q 40/02 - Opérations bancaires, p. ex. calcul d'intérêts ou tenue de compte
G10L 13/02 - Procédés d'élaboration de parole synthétiqueSynthétiseurs de parole
Webpage integrity is monitored using hash verification. A hash verification process is implemented to detect unauthorized changes to value field(s) in a webpage's source code and, while the user is conducting an active web session on the webpage, an alert, which may be communicated via the webpage, is generated and communicated to a user in response to determining that there was an unauthorized change.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
Systems and methods are disclosed for a card device that integrates eSIM technology and Distributed Ledger Technology (DLT) to provide a secure, flexible solution for handling transactions across multiple financial institutions (FIs). The card system associates a single, secure eSIM-enabled card with multiple accounts and FIs, enhancing transaction security and efficiency. The card, embedded with an eSIM, allows dynamic association with customer details and FI accounts, ensuring each transaction is authenticated on a decentralized platform without sharing sensitive information. The system employs DLT for logging transaction details and managing transaction metadata centrally, providing fraud detection and real-time settlement capabilities. The invention improves security by using cryptographic methods and real-time monitoring including geo-locating of cards and clones to prevent unauthorized access and fraud, addressing the need for a secure, multi-institution financial transaction platform.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Various aspects of the disclosure relate to verification of data sets used for real-time processes and/or batch processes. A computing platform negotiates, by a first quantum node, a shared key group with at least a second quantum node and calculates an exclusive or (XOR) value of a pair of the first quantum node and the second quantum node. The first quantum service node performs a shared key grouping with the second quantum node and then selects a quantum key relay link between a real-time node and a batch source node. The computing platform selects a corresponding state of all virtual quantum nodes associated with the quantum key relay link and encapsulates a virtual quantum link state between any two quantum service nodes in the quantum network into a database decision engine data file.
Various aspects of the disclosure relate to dynamically determining user access levels to manage access to enterprise information via application programming interfaces (APIs). A neuro-symbolic AI-based assessment enabled system manages assessments and response to API calls to ensure data security of information shared with external sources via the API. This system identifies and analyze access patterns via neural networks and symbolic reasoning to dynamically manage a rule set to determine access levels and corresponding data sub-objects that are built in real time to be shared with an API response message.
Various aspects of the disclosure relate to dynamically determining user access levels to manage access to enterprise information via application programming interfaces (APIs). A neuro-symbolic AI-based assessment enabled system manages assessments and response to API calls to ensure data security of information shared with external sources via the API. This system identifies and analyze access patterns via neural networks and symbolic reasoning to dynamically manage a rule set to determine access levels and corresponding data sub-objects that are built in real time to be shared with an API response message.
A system includes a memory configured to store one or more cyber threat scenarios associated with a software application of a plurality of software applications. The system further includes processors for accessing the one or more cyber threat scenarios, identifying, based on the one or more cyber threat scenarios, an actual cyber threat associated with an execution of the software application in accordance with the current configuration, and, in response, executing a dynamic remote based isolation (RBI) engine configured to perform a dynamic reconfiguration of the software application and the system components in response to the identified actual cyber threat. The dynamic reconfiguration is different from the current configuration of the software application and the system components. The processors further cause the software application to be executed in accordance with the dynamic reconfiguration of the software application and the system components.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
Virtual machine images may be constantly scanned using background process, to identify current and evolving security risks, such as by optimizing the image scanning a last-in, first-out (LIFO) stack to prioritize most relevant images. Older and/or non-relevant image are removed from the scanning process and removed from use. Virtual machines image prioritization is based on each virtual machine image's current and/or potential usage requirement, where the LIFO stack prioritizes the scanning order. Newly created virtual machine images and/or newly re-activated virtual machine images are placed onto a provisioning queue (first-in, first out) before activation. The virtual machine images active within a host computing environment are processed via a reconciliation process to scan for indications of security vulnerabilities and/or threats to network security. Obsolete or otherwise irrelevant virtual machine images are removed from use via a repository synchronization process.
A system for creating a controllable output summary of text is disclosed. The system generates a set of summaries of text and for a first summary from among the set of summaries, executes a script that is configured to append the first summary to a set of summary-title pairs. The system generates a first title associated with the first summary in response to executing the script. The system compares the first title with the text. Based at least on the comparison, the system determines if the title indicates the context of the text. If it is determined that the title indicates the context of the text, the system generates a dataset of title-text pairs including the first title paired with the text. The system trains a target summarization algorithm with the generated dataset.
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to receive information parameters associated with a machine learning (ML) model of the one or more ML models and execute an ML algorithm to evaluate the information parameters in accordance with one or more latency classification operations. The one or more latency classification operations are configured to determine whether the ML model comprises multiple latency complications. Further, the processor is configured to generate multiple analysis results indicating that the ML model comprises the latency complications in response to evaluating the information parameters, determine a latency cause of the latency complications based on the analysis results, and determine multiple corrective operations configured to correct the latency cause. The processor is configured to update the ML model to comprise the corrective operations and generate a report configured to release an updated version of the ML model.
Systems, computer program products, and methods are described herein for the systematic splicing of original content into frames and the insertion of blank non-fungible token (NFT) tagged frames at critical points within the multimedia preventing Artificial Intelligent (AI) tool modification of an original multimedia. The invention is configured to prevent content editing using blank NFT token frame insertion, providing NFT integration for all multimedia digitally rendered. Each multimedia frame is associated with a unique NFT, creating a digital fingerprint for authentication. Blank NFT frames are strategically inserted throughout the multimedia based on criticality of the frame to the overall multimedia, forming a grid pattern. The system implements distributed ledger technology where NFT information is stored on a ledger for transparency and immutability. Upon source key recognition replacement frames will replace blank NFT frames in real time through consortium network to render at a releasing entity end point.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
91.
SYSTEMS AND METHODS FOR DYNAMIC PROTECTION OF WIRELESS COMMUNICATION PROTOCOLS UTILIZING STEGANOGRAPHIC KEYS AND DUAL-LAYER CERTIFICATE AUTHENTICATION
Systems, computer program products, and methods are described herein for dynamic protection of wireless communication protocols utilizing steganographic keys and dual-layer certificate authentication. The present disclosure is configured to identify the type of network to which a user device is connected, determine whether the network is approved, public, or captive, and provide a recommendation to enable wireless protection mode for untrusted networks. The system generates an on-demand protection key via a steganography server and signs it using a wireless protection certificate through a “Key in Key” (KIK) mechanism. The transaction application validates the certificate and encrypts sensitive transaction data using the on-demand key. Only packets that successfully validate the certificate are processed, while others are ignored. This dual-layer authentication prevents unauthorized packet-in-packet attacks and ensures data integrity and confidentiality across various wireless networks.
Aspects related to machine learning-based script interruption handling are provided. A computing platform may train a machine learning model to identify, for a test script interruption, a corrective action to resolve the interruption. The platform may receive information and details corresponding to an interruption associated with a test automation script. The platform may identify, by executing a machine learning model, a cause of the interruption and a predicted corrective to resolve the interruption. The platform may cause, based on identifying the predicted corrective action, initiation of the corrective action. The platform may update, based on the corrective action, the machine learning model. The platform may also resume the test automation script from the point of interruption.
An intelligent and multi-layered approach that uses real-time analysis to identify and confirm the authenticity and inauthenticity of bulk digital documents. Support Vector Machine (SVM) learning is implemented to perform significant attribute validations, such as barcode validation, image-specific validations, and signature validations. An SVM classifier is implemented to compare, analyze, predict the accuracy of the document (i.e., quantify the certainty of authenticity) and decision the documents as either valid/authentic or invalid/tampered-state. Neuro-symbolic Artificial Intelligence (AI) technology is subsequently implemented to confirm or deny the authenticity decision resulting from the SVM classifier.
G06V 20/00 - ScènesÉléments spécifiques à la scène
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p. ex. de formulaires ou de tableaux d’entreprise
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
94.
MACHINE LEARNING-BASED PLATFORM TO DETECT AND HANDLE VOLUMETRIC ATTACKS
Aspects related to a machine learning-based platform to detect and handle volumetric attacks are provided. A volumetric attack detection and handling platform may train a machine learning model to identify and/or predict volumetric attacks, generate predicted corrective actions, and execute actual corrective actions. The platform may receive information of a network request corresponding to a volumetric attack or a request from a legitimate user. The platform may identify a correlation of volumetric attack and/or legitimate requests using the model. The platform may further identify a predicted corrective action using the model. The platform may cause, based on identifying the predicted corrective, initiation of a response to the malicious traffic request. The response to the malicious traffic request may comprise implementing an actual corrective action generated by the model. The platform may update the machine learning model based on the information of recent requests and corrective actions.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
95.
SYSTEM AND METHOD FOR AUTOMATED TEST CASE GENERATION USING A HYBRID ARTIFICIAL INTELLIGENCE MODEL
A system is provided for automated test case generation using a hybrid artificial intelligence model. In particular, the system may comprise an automated test generator (“ATG”) that may automatically generate test cases or scenarios using one or more artificial intelligence (“AI”) models. In this regard, a user may input a high level test scenario into the ATG. Subsequently, the ATG may use a hybrid model (e.g., a model combining multiple transformer models) to generate complex and comprehensive test cases based on the user input. In some embodiments, the ATG may use an AI accelerator processing unit to increase the speed of the test case generation and refinement processes. In this way, the system provides an expedient, efficient way to generate complex test cases for software testing applications.
A system includes a memory configured to store a set of application environment parameters associated with a software application of a plurality of software applications. The system further includes processors for accessing the set of application environment parameters associated with the software application, identifying, based on the set of application environment parameters, a plurality of potential threats and vulnerabilities associated with an execution of the software application in accordance with the current configuration, and executing one or more generative machine-learning models trained to generate a prediction of one or more cyber threat scenarios based on the set of application environment parameters and the plurality of potential threats and vulnerabilities. The prediction of the one or more cyber threat scenarios includes cyber threat scenarios specific to the software application. The processors further output, by the one or more generative machine-learning models, the prediction of the one or more cyber threat scenarios.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
Systems and methods for an integrated, multi-channel, conversational utility are provided. Methods include providing a single search icon on a user device accessing an online portal. Methods include receiving a conversational input inquiry and, via a specially trained ML model, generating a first set of results including at least one general information resource result and at least one user-specific information result. When the first set of results exceeds a threshold confidence score, methods include displaying the first set of results as a response to the input inquiry. When the confidence score fails to exceed the threshold score, methods include generating a conversational follow-up question designed to clarify the intent of the input inquiry, receiving a response to the follow-up question, generating a second set of results and, when the second set of results exceeds the threshold confidence score, displaying the second set of results as the input inquiry response.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/9538 - Présentation des résultats des requêtes
98.
Attribute recharacterization in individual portions of images
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to generate a tag for a portion of peripheral information, determine a correlation between the peripheral information and the tag and execute a machine learning algorithm in response to determining that an amount of information preserved is outside an accuracy tolerance to determine at least one difference between the peripheral information and the communication information, evaluate the at least one difference against historical data associated with the network device, determine multiple tagging commands based on an evaluation of the at least one difference against the historical data and modify the tag to incorporate the possible modifications, and generate a portion of the communication information based on the portion of the peripheral information in accordance with a modified version of the tag and transmit the portion of the communication information to the network device.
Arrangements for using generative artificial intelligence models for ATM process generation are provided. In some examples, a computing platform may receive, from at least one image or measurement capture device, dimension data associated with an ATM. The ATM may have a plurality of components arranged on a face of the ATM. The dimension data may be input to a generative artificial intelligence model and the model may be executed to output, based on the dimension data, a position or location of each ATM component relative to a reference point on the ATM. In some examples, the model may further output at least one audio script describing the location of each component. The model may output one or more translations of the at least one audio script. The computing platform may transmit or send the at least one audio script to the ATM for presentation during user interaction with the ATM.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
100.
SYSTEM FOR ADVANCED NETWORK TRAFFIC ANALYSIS IN A COMPUTING ENVIRONMENT
Systems, computer program products, and methods are described herein for advanced network traffic analysis in a computing environment. The present disclosure is configured to retrieve, from a traffic data log of a Web Application Firewall (WAF), information associated with a blocked traffic instance; implement, using a code analysis subsystem, a security testing protocol on a host application associated with the blocked traffic instance; determine an exposure associated with the host application based on at least implementing the security testing protocol; generate a notification comprising information associated with the exposure; and transmit a signal configured to cause a computing device associated with the host application to display the notification.
