Enabling modifications to smart contracts within a distributed trust computing network platform. Enablement of smart contract modifications is made possible by generating a smart contract and an associated hash value and storing such in an intermediate data block held within a staging area. The intermediate data block is held in the staging area until (i) all the parties accept the smart contract and (ii) the conditions are met and the smart contract self-executes. As long as the intermediate data block remains in the staging area, the data stored therein is subject to modification. Once the parties to the smart contract accept the smart contract (and/or modifications to the smart contact) and the conditions are met, such that the smart contact self-executes, the intermediate data block is synthesized/transformed into an immutable data block which is stored within a distributed ledger of the corresponding distributed trust computing network.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
2.
SYSTEM AND METHOD FOR GENERATING ALTERNATIVE INFORMATION FORMATS USING ADVANCED COMPUTATIONAL MODELS FOR DATA ANALYSIS AND AUTOMATED PROCESSING
Systems, computer program products, and methods are described herein for generating alternative information formats using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive a message, wherein the message comprises one or more content components; transmit the message to an alternative information module, wherein the alternative information module comprises an alternative information database and an artificial intelligence module; determine, using the artificial intelligence module, an alternative information format, wherein the alternative information format is based on the message, and wherein the alternative information format comprises a natural language that uses the visual-manual modality to convey meaning; transmit the message to a sequencing module, wherein the sequencing module integrates the alternative information format into appropriate segments of the message; and create an overlayed communication, wherein the overlayed communication comprises the message and the alternative information format.
Embodiments of the invention provide a comprehensive system for monitoring, evaluating, and managing code changes in a software development environment. The system comprises a Code Monitoring Subsystem (CMS) that continuously scans servers to identify active jobs and issues alerts based on various conditions. A Code Resolution Subsystem (CRS) aids developers in resolving issues and may include a machine learning (ML) subsystem for suggesting code options. The system also features a Parallel Code Monitoring Subsystem (PCMS) that generates atomic versions of code changes for real-time collaboration among developers. Containers corresponding to code changes are created and subjected to specific tests, with quality assessed through smart contracts. A composite value, serving as a metric for assessing a container's susceptibility to errors, is determined for each container. The system enhances code quality, reduces duplication, and facilitates efficient development.
Systems, computer program products, and methods are described herein for steganalysis detection of metadata in a video stream for providing real-time data. An encrypted steganalysis marker is positioned within a boarder of a video stream and, upon user device scanning and identification provides a communication channel for real-time data display on the user device. The data displayed on the user device is transmitted via narrowband internet-of-things communication linkage displaying product or service data associated with the video stream. Using a combination of NB-IoT and computational memory computing creates a unique, in user device computing structure with various variable inputs to provide specified data and recommendations to the user.
H04N 21/2389 - Traitement de flux multiplexé, p. ex. cryptage de flux multiplexé
H04N 21/258 - Gestion de données liées aux clients ou aux utilisateurs finaux, p. ex. gestion des capacités des clients, préférences ou données démographiques des utilisateurs, traitement des multiples préférences des utilisateurs finaux pour générer des données collaboratives
H04N 21/8358 - Génération de données de protection, p. ex. certificats impliquant des filigranes numériques
5.
SYSTEM AND METHOD FOR DETERMINING AND PREVENTING MALFEASANT ACTIVITY IN A PRIVATE DISTRIBUTED NETWORK
Systems, computer program products, and methods for determining and preventing malfeasant activity in a private distributed network. The method includes generating one or more executed data transfer records for each of one or more executed data transfers across a distributed network. Each of the one or more executed data transfer records includes one or more data transfer information fields. The method also includes generating one or more decoy executed data transfer records. The decoy executed data transfer record(s) includes the data transfer information field(s). The method further includes providing a portal that contains each of the records associated with the distributed network. The method still further includes detecting a record access for one or more of the decoy executed data transfer records by an end-point device associated with a user. The method also includes causing an escalation action to be executed based on the detection of the record access.
Embodiments of the present invention provide a system for generating on-demand single-use biometric authentication credentials. The system is configured for determining initiation of an authentication request to access a resource from a user device of a user, prompting the user to select a type of authentication credential from one or more types of authentication credentials, receiving a selection of the type of the authentication credential, instantaneously generating a single-use unique authentication credential associated with the type of the authentication credential, via one or more machine learning models, and transmitting the single-use unique authentication credential to the user device for use in authentication of the user in gaining accessing to the resource.
Various aspects of the disclosure relate to creation and management of virtualized accounts. A virtualized account framework implemented on a computing platform provides an interface for real-time user configuration and account creation, deletion, and management actions. A core account may be linked to an existing account managed by an account management system or may be newly created. Each core account may be associated with a data structure defining one or more virtual accounts associated with the core account. Balance allocation from the core account to each of the virtual accounts, distribution limitations, balance limits from the core account to each of the virtual accounts may be defined by rules linked to the data structure. Virtual accounts, and in some cases, core accounts, may be redefined in real time, where account management upon reassignment is associated with a different account management system.
Systems, methods, and apparatus are provided for generating dynamic metaverse accommodations using artificial intelligence. A user device may initiate a metaverse session. Deep learning networks may derive a user profile based on data from the user device and generate a set of samples from the user profile. The generated samples may include user characteristics and avatar features associated with the user characteristics. The generated samples may be used to train a multitask machine learning model. Deep learning networks may generate a metaverse accommodation targeted to the user profile. The accommodation may be rendered in the metaverse environment. The accommodation may be transmitted to an actuator at the user device. The accommodation may be stored in association with user characteristics in a distributed ledger.
G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
9.
MEMORABLE SECURE, AND STRONG PASSWORD GENERATOR ENHANCED WITH GAMIFICATION AND MACHINE LEARNING
Systems and methods for automating the generation of a strong, secure, and memorable password using gamification. Systems may include a computer configured to receive words and phrases from a user using a gamification tool, use a machine learning model to eliminate words and phrases found when searching open-source intelligence (OSINT) available about the user, use the machine learning model to identify portions of the non-eliminated units of information, and use the machine learning model to combine the portions into memorable password options. Systems may include the computer configure to use the machine learning model to eliminate any of the password options found when searching OSINT, present a subset of the non-eliminated password options to the user, receive the selected password from the user, use the machine learning model to generate an obfuscated reminder for the selected password, and provide the obfuscated reminder to the user.
G06F 21/46 - Structures ou outils d’administration de l’authentification par la création de mots de passe ou la vérification de la solidité des mots de passe
10.
ASSEMBLING AND DEPLOYING COMPUTING TASKS LEVERAGING SWARM INTELLIGENCE
Apparatus and methods for assembling and deploying computing tasks using swarm intelligence are provided. A swarm intelligence network program may be installed on multiple automated teller machines (“ATMs”) within a geographical area. When one of the ATMs loses connectivity with its financial institution, the ATM may create an ad-hoc swarm intelligence-based network with the other ATMs. The ad-hoc network may include a distributed ledger. The ATM may determine that a customer request for a financial transaction is valid and complete the request and record the transaction on the distributed ledger. The ATM may use hardware and software resources from the other ATMs on the ad-hoc network.
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 20/38 - 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
11.
SECURE AUTHENTICATION AND INTEROPERABILITY MODEL FOR MACHINE TO MACHINE ("M2M") COMMUNICATION
A network of nodes supporting machine to machine (“M2M”) communication within the network is provided. Each of a plurality of nodes within the networks may be in an inactive communication state prior to authentication. The authentication may be performed by a remote central node (“RCN”). The RCN may be configured to control authentication and communication between nodes in the network. The RCN may perform one, two or more methods of authentication to securely authenticate each node. Following authentication, the RCN may generate network protocol for data payloads transmitted within the network. The RCN may further be configured to store data transmitted between nodes and maintain or delete the data based on a level of privacy that may be tagged to the stored data.
Arrangements for pre-authenticating users to interactive voice response (IVR) systems are provided. In some examples, a computing device may receive and store a valid telephone number associated with an enterprise organization IVR system and an enterprise organization application programming interface (API) access key. A request to initiate a communication session with the IVR system may be received and the request may include a telephone number. If the telephone number matches the valid telephone number, an API call to the enterprise organization may be made and a one-time passcode (OTP) may be received. The telephone number may be appended to include the OTP as a suffix and the communication session with the IVR system may be initiated. The IVR system may extract the OTP and validate the OTP. If the OTP is validated, the communication session may be initiated as a pre-authenticated call.
Methods, apparatus, and systems for active and passive monitoring of a mainframe network are provided. The methods may include monitoring, using a mainframe management system, one or more individual applications executing on the mainframe network. The methods may include receiving, at the mainframe management system, a set of search parameters. The methods may include inputting the set of search parameters into a search function within the mainframe management system. The methods may include executing a search corresponding to the set of search parameters. The methods may include identifying a data entry list. The data entry list may include data lines that correspond, over a threshold value of similarity, to the set of search parameters. The methods may include outputting, in real-time, the data entry list. The method may include displaying the data entry list on a display operating in tandem with the mainframe management system.
Systems and methods for automating generation of a strong and memorable password. Systems may include a computer configured to receive units of information from the user, use a machine learning model to eliminate units of information found when searching open-source intelligence (OSINT) available about the user, use the machine learning model to identify portions of the non-eliminated units of information, and use the machine learning model to combine the portions into memorable password options. Systems may include the computer configure to use the machine learning model to eliminate any of the password options found when searching OSINT, present a subset of the non-eliminated password options to the user, receive the selected password from the user, use the machine learning model to generate an obfuscated reminder for the selected password, and provide the obfuscated reminder to the user.
G06F 21/46 - Structures ou outils d’administration de l’authentification par la création de mots de passe ou la vérification de la solidité des mots de passe
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.
Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.
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
Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.
A network security computing system includes a steganographic communications analysis engine monitoring incoming and outgoing messages on a secure computing network. The steganographic communications analysis engine identifies a pattern of file transfers between a first computing device on the secure computing network and an internal or external message recipient. When a pattern is identified, the steganographic communications analysis engine quarantines an associated computing device from the secure network. The steganographic communications analysis engine analyzes files transferred between the computing device and the recipient for indications of steganographic information and causes display, based on an identified indication of steganography, an indication that the computing device had been compromised by command and control malware.
Embodiments of the present invention provide a system for securely authenticating users using quantum key distribution protocol. The system is configured for receiving an authentication request comprising at least one credential from a user, via a user device, calculating an authentication match score for the at least one credential, retrieving an authentication token associated with the user stored on an external physical device connected to the user device, retrieving an enrollment match score associated with the authentication token of the user, validating the at least one credential by comparing the authentication match score of the at least one credential with the enrollment match score associated with the user, determining that the validation is not successful, and performing a quantum key distribution secret verification based on an enrollment common base stored on a quantum computing platform during the enrollment phase via a quantum communication network.
Systems, computer program products, and methods are described herein for a decentralized machine learning source code generation framework via a holochain network. The present invention is configured to receive a predetermined code criteria, receive a new code segment from an editor on an endpoint device, retrieve characteristics of the new code segment, determine, using a trained machine learning model, at least one subsequent code segment, based on at least the characteristics of the new code segment, determine, using an evaluation engine, at least one score of the subsequent code segment, wherein the at least one score is associated with the predetermined code criteria, and transmit to the editor of the endpoint device for displaying a predetermined number of the at least one subsequent code segments above a predetermined threshold of the at least one score.
An automated solution is provided through quantum computing, AI/ML algorithms, neural networking, and hybrid computing integration in order to provide end-to-end optimization software programs. The system may be implemented by generating unique grade(s) for software program(s) against disparate behavior using quantum computing. Quantum entanglement and superposition will ensure fast calculation and analysis of every code snippet. The grade can be further utilized by classical computing engines, which can operate in layers to generate an intelligent report highlighting granular deviation and select an optimized version of program through decision making algorithms, which can then be integrated to original version after passing validity/compatibility checks and automatically employed.
Arrangements for pre-authenticating users to interactive voice response (IVR) systems are provided. In some examples, a user may initiate, via an application executing on a mobile device of the user, a telephone call to an IVR system. A computing platform may intercept the call and may generate a one-time passcode (OTP). The OTP may be appended to the telephone number as a suffix and the telephone call may be initiated with the IVR system using the telephone number and appended suffix. The IVR system may extract the OTP and may validate the OTP. If the OTP is validated, the call may be initiated as a pre-authenticated call in which the IVR system might not request authentication data from the user. If the OTP is not validated, the call may be initiated as a standard call in which the IVR system may request authentication data from the user.
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
H04M 3/42 - Systèmes fournissant des fonctions ou des services particuliers aux abonnés
H04M 3/436 - Dispositions pour intercepter des appels entrants
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
23.
SYSTEMS AND METHODS FOR DATA TRACE AND SEQUENCE DETERMINATIONS IN DISTRIBUTED NETWORKS
Systems, methods, and computer program products are provided herein for data trace and sequence determinations in distributed networks. An example method includes receiving a request for an interaction determination and determining a plurality of distributed service systems associated with the interaction. The plurality of distributed service systems include a sequence defining an order by which operations associated with the interaction are performed by respective distributed service systems and each of the distributed service systems includes trace agents that generate service system specific data trace objects. The method further includes capturing the one or more service system specific data trace objects for each of the distributed service systems and generating an interaction object based on the service system specific data trace objects for each of the distributed service systems associated with the interaction.
Methods and systems are provided for restoring a source database to a target environment. The methods and systems may include calculating an amount of data on each drive of the source database. The methods and systems may include calculating free space of each drive of the target environment. The methods and systems may include shrinking filegroups in the drives of the source database. The methods and systems may include fetching historical transactional queries run on tables in the filegroups. The methods and systems may include identifying interdependencies between tables using the queries. The methods and systems may include ingesting, by an AI engine, the calculations, the queries, the identified interdependent tables, historical information of table movement and a business use case. The methods and systems may include the AI engine determining how to restore the source database using the ingested information.
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 16/22 - IndexationStructures de données à cet effetStructures de stockage
25.
SYSTEM AND METHOD FOR DETERMINING OPTIMAL RESOURCE TRANSFER ROUTING USING QUANTUM GATEWAY OPTIMIZATION
Systems, computer program products, and methods are described herein for determining optimal resource transfer routing using quantum gateway optimization. The present disclosure is configured to receive a resource transfer request associated with transferring a resource from a submitting device to a receiving device, wherein the resource transfer request comprises resource transfer instructions and resource transfer metadata; determine, in response to the resource transfer request, an optimized gateway route, wherein the optimized gateway route defines a series of gateways that the resource to be transferred may be processed, and wherein determining the optimized gateway route comprises analyzing the resource transfer instructions, resource transfer metadata, and one or more gateway route characteristics; and complete the resource transfer request, wherein completing the resource transfer request, wherein completing the resource transfer request comprises transferring the resource from the submitting device to the receiving device via the optimized gateway route.
Methods and systems are provided for managing access to a file. The methods and systems may include locking access to the file using a password accessible security setting. The methods and systems may include designating a password as an unlock password. The methods and systems may include communicating the password to a first group of users. The methods and systems may include providing a prompt to input the unlock password upon a request to access the file. The methods and systems may include providing access to the file in response to inputting the unlock password. The methods and systems may include authenticating each unauthenticated user that inputs the unlock password. The methods and systems may include deactivating the password as the unlock password. The methods and systems may include removing authentication from a user in response to the user meeting a predetermined condition.
A computing platform may train an LLM by performing a plurality of clustering iterations. The computing platform may record, using a distributed ledger and for each of the plurality of clustering iterations, information of the corresponding clustering iteration. The computing platform may test the LLM, which may reveal at least one error in the LLM. The computing platform may identify, using the distributed ledger, a clustering iteration corresponding to the at least one error and information associated with the clustering iteration. The computing platform may identify, based on the clustering iteration corresponding to the at least one error and the information associated with the clustering iteration, a remediating action. The computing platform may update the LLM by performing the remediating action. The computing platform may retest the LLM. Based on identifying that an accuracy of the LLM meets or exceeds an accuracy threshold, the computing platform may deploy the LLM.
A computing platform may obtain, from an information storage source, historical information, which may be structured rather than unstructured. The computing platform may train, using the historical information, a foundational artificial intelligence (AI) model. The computing platform may select one or more features of the foundational AI model for use in training a generative AI model. The computing platform may identify a portion of the historical information corresponding to the selected one or more features. The computing platform may normalize the portion of the historical information. The computing platform may train, using the normalized portion of the historical information, the generative AI model. The computing platform may receive, from a user device, a generative AI prompt. The computing platform may generate, by inputting the generative AI prompt into the generative AI model, a generative AI response. The computing platform may send, to the user device, the generative AI response.
Systems, methods, and apparatus are provided for a secure multicloud test automation framework. The automation framework may receive a natural language request for a cloud-based test scenario at a user interface on an enterprise network. The test scenario may include a cloud resource and a cloud platform. Machine learning may map keywords extracted from the test scenario to a set of test cases associated with the cloud resource. Keyword mapping may also identify a configuration file associated with the cloud platform. The automation framework may retrieve shell scripts specified by the set of test cases from a shell script repository. The automation framework may use data from the configuration file to access the cloud platform via a secure gateway and execute the shell scripts using data from the cloud platform. The automation framework may generate a comprehensive summary report and maintain technical logs for the test.
In conventional networked computing systems, stream-processing software is utilized to handle real-time data feeds. For example, a stream-processing software may sort incoming data feeds into data logs, which are then consumed by various application servers within the computing system. However, this consumption process is susceptible to failure as application servers often fail to consume a full payload of data comprising a particular message. As such, a need exists for a streaming architecture with improved fault tolerance. The system provided herein solves the problem via a reliable streaming process, which regularly generates partitions within a series of data lakes. As streaming data is received, the payloads are synced into the different data lakes based on metadata associated with the streaming data. The system can then perform individual quality checks on each partition of data, enabling the system to continuously monitor data quality over time.
Systems, computer program products, and methods are described herein for maintaining security of virtual objects in a distributed network. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine viewing angles of avatars moving along access paths in a virtual world and a second artificial intelligence engine configured to determine movements of the avatars moving along the access paths in the virtual world. The system may include a third artificial intelligence engine configured to generate visual content based on attributes of users associated with the avatars, the access paths, the viewing angles of the avatars moving along the access paths in the virtual world, and the movements of the avatars moving along the access paths in the virtual world.
Systems, computer program products, and methods are described herein for maintaining security of virtual objects in a distributed network. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine motives of users associated with avatars in a virtual world and a second artificial intelligence engine configured to determine access paths of the avatars in the virtual world. The system may include a third artificial intelligence engine configured to generate visual content based on attributes of the users, the motives of the users, and the access paths of the avatars. The system may be configured to detect diversions from access paths, determine updated motives of users, determine whether the diversions are permissible, and restrict movement of the avatar within the virtual world.
A computing platform may obtain, from an information storage source, historical information, including both structured information and unstructured information. The computing platform may train, using the historical information, a foundational AI model. The computing platform may select features of the foundational AI model for use in training a plurality of generative AI models. The computing platform may identify a portion of the historical information corresponding to the selected features. The computing platform may normalize the portion of the historical information, and may train, using the normalized portions of the historical information, each generative AI model of the plurality of generative AI models. The computing platform may receive, from a user device, a generative AI prompt. The computing platform may generate, by inputting the generative AI prompt into one of the plurality of generative AI models, a generative AI response, and may send, to the user device, the generative AI response.
A method and system for detecting counterfeit money may include an automated teller machine (ATM) including an olfactory sensor configured to detect counterfeit notes and valid notes, an olfactory signature database comprising counterfeit note olfactory signatures and valid note olfactory signatures, wherein the ATM may be in communication with the olfactory signature database, and wherein the olfactory sensor via the ATM detects and transmits olfactory note signatures to the olfactory signature database, and wherein the ATM is configured to reject a detected counterfeit note for deposit.
G07D 7/14 - Vérification spécialement adaptée à la détermination de l’identité ou de l’authenticité de papiers de valeur ou pour discriminer ceux qui sont inacceptables, p. ex. qui ne correspondent pas à une monnaie à l'aide de moyens chimiques
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
35.
System and method for performing a secured operation
A system for performing secured operations includes a user device and a server. The user device generates a first operation data that comprises the origin of the operation and a unique identifier of a user. The user device communicates the operation data to the server. The server generates, based on the first operation data, one or more first conditional rules that comprise a first rule that indicates the operation is to be executed when a second user requesting to receive a data item is identified. The server determines that one or more first conditional rules are met. In response, the server communicates a signal to the user device, where the signal indicates to transfer the data item to a second user device associated with the second user.
A system for implementing traceability to a data item comprises a user device and a gateway server. The user device appends headers to a data packet that includes the data item. The headers comprise parameters including origin information associated with the user device and a user. The gateway server receives the data packet and compares each parameter with a counterpart parameter from a list of expected parameters. The gateway server determines whether more than a threshold number of the parameters corresponds to counterpart parameters from among the list of expected parameters. In response to determining that more than the threshold number of the parameters correspond to counterpart parameters from among the list of expected parameters, the gateway server appends a second header to the data packet, where the second header indicates that the data packet is verified. The gateway server communicates a request message that includes the data packet.
A system for validating the origin information of a data item accesses a data packet that indicates a request to transfer a data item. The data packet is appended with a first header and a second header. The first header comprises information about the sender of the data packet. The second header comprises information about a user device from which the data packet has originated. The system compares the information about the sender of the data packet with previously provided user information and determines that the user information corresponds to the information about the sender. The system communicates a request that indicates whether the information about the user device is valid and receives a message that indicates the information about the user device is valid. In response, the system communicates a message that comprises the data packet and instructions that, upon execution, cause the data packet to be transferred.
A method includes receiving a hash of a static password and a hash of a lot-one authentication string from a user device of a user. After an initial validation, an authentication matrix is generated. A block selection process is performed to select spurious and authentication blocks from the authentication matrix. The authentication blocks are selected based on a lot-two authentication string associated with the lot-one authentication string. In response to determining that the spurious and authentication blocks are selected according to a block selection sequence stored in a user profile of the user, a dynamic password is generated by combining the static password, the lot-one authentication string, and the authentication blocks. A hash of the dynamic password is generated. In response to determining that the hash of the dynamic password matches a hash of a dynamic password that is stored in the user profile, the user is authenticated.
A method includes receiving hashes of a static password and a lot-one authentication string from a user device of a user. After an initial validation, a first authentication matrix (AM) is generated. A block selection process is performed to select spurious and authentication blocks. While performing the block selection process, the first AM is replaced by a second AM, such that a first authentication block is selected from the first AM based on a first lot-two authentication string and a second authentication block is selected from the second AM based on a second lot-two authentication string. A dynamic password is generated by combining the static password, the lot-one authentication string, and the authentication blocks. A hash of the dynamic password is generated. In response to determining that the hash of the dynamic password matches a hash of a dynamic password stored in a user profile, the user is authenticated.
G06F 21/54 - 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 par ajout de routines ou d’objets de sécurité aux programmes
40.
SYSTEMS AND METHODS FOR DETERMINING A COMPUTING SYSTEM’S CURRENT STATE BY IMPLEMENTING STATE MACHINES AND KNOWLEDGE GRAPHS IN AN ELECTRONIC ENVIRONMENT
Systems, computer program products, and methods are described herein for determining a computing system's current state by implementing state machines and knowledge graphs in an electronic environment. The present disclosure is configured to identify at least one knowledge graph comprising a plurality of clusters associated with at least one computing system, each cluster comprises a plurality of state machines associated with the at least one computing system; identify data associated with the computing system; apply the data associated with the computing system to at least one state machine; generate at least one output associated with the computing system; compare the at least one output with at least one pre-defined output; generate a confidence level for the at least one current state attribute; and determine a current state attribute for the computing system, wherein the current state attribute defines a current state of the computing system.
Systems, computer program products, and methods are described herein for detecting attrition in a distributed network using artificial intelligence. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine indicators of relationships between users and entities and a second artificial intelligence engine configured to determine statuses of relationships between the users and the entities. The system may determine, using the first artificial intelligence engine, and based on data associated with interactions between a user and an entity, a plurality of indicators of a relationship between the user and the entity. The system may determine, based on the plurality of indicators, based on the data associated with the interactions between the user and the entity, and using the second artificial intelligence engine, a status of the relationship between the user and the entity.
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
G06Q 30/015 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance
G06Q 30/0202 - Prédictions ou prévisions du marché pour les activités commerciales
42.
INTELLIGENT METHOD TO COMBINE MULTIPLE BLOCKCHAIN BASED SMART CONTRACTS LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE
Aspects of the disclosure relate to using machine learning models to merge smart contracts. A computing system may receive a prompt to merge smart contracts. Based on inputting the prompt into a generative artificial intelligence model configured to parse prompts, smart contract data may be retrieved from a blockchain stored in a distributed ledger platform. Based on inputting the smart contract data into the generative artificial intelligence model, smart contract clusters may be generated. Based on at least one of the smart contract clusters meeting performance criteria, merged smart contracts that meet the performance criteria may be generated. Furthermore, one or more blocks comprising the merged smart contracts may be generated.
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
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
43.
SYSTEMS AND METHODS FOR MAINTAINING SECURITY OF VIRTUAL OBJECTS IN A DISTRIBUTED NETWORK
Systems, computer program products, and methods are described herein for maintaining security of virtual objects in a distributed network. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine motives of users associated with avatars in a virtual world and a second artificial intelligence engine configured to determine access paths of the avatars in the virtual world. The system may include a third artificial intelligence engine configured to determine viewing angles of the avatars moving along the access paths in the virtual world and a fourth artificial intelligence engine configured to generate visual content based on attributes of the users, the motives of the users, the access paths of the avatars, and the viewing angles of the avatars moving along the access paths in the virtual world.
G06F 3/04815 - Interaction s’effectuant dans un environnement basé sur des métaphores ou des objets avec un affichage tridimensionnel, p. ex. modification du point de vue de l’utilisateur par rapport à l’environnement ou l’objet
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06T 13/40 - Animation tridimensionnelle [3D] de personnages, p. ex. d’êtres humains, d’animaux ou d’êtres virtuels
Arrangements for biometric data-based holographic authentication are provided. In some examples, biometric data for a plurality of users may be received. A computing platform may receive a request to process an event. In response to receiving the request to process the event, the computing platform may retrieve biometric data of a requesting user and generate, based on the biometric data, a hologram of the biometric data of the user. In some examples, the hologram may be displayed on a device and provided to an authentication reader device as authentication data. The authentication reader device may capture an image of the hologram and the computing platform may receive the image. The computing platform may compare the captured image of the hologram to the generated hologram to determine whether there is a match. If not, the requested event may be denied. If so, the event may be processed.
G03H 1/00 - Procédés ou appareils holographiques utilisant la lumière, les infrarouges ou les ultraviolets pour obtenir des hologrammes ou pour en obtenir une imageLeurs détails spécifiques
G06F 21/16 - Traçabilité de programme ou de contenu, p. ex. par filigranage
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
45.
SYSTEM FOR AUTOMATED COMPUTER SOFTWARE RELEASE VALIDATION AND MANAGEMENT
A system is provided for automated computer software release validation and management. In particular, the system may receive and aggregate data from various computing resources within the network environment, such as computing applications. Based on the data, the system may determine which resources may be affected by a software release that is set to be deployed to the production environment. The system may further receive user inputs in the form of artifacts associated with one or more checkpoints used in a validation process associated with the software release. The system may then, through a reporting engine, provide a visualization of the data and checkpoints through a dashboard to provide a real-time status of the validation process. In this way, the system provides an efficient and transparent way to validate and manage computer software releases.
Systems, computer program products, and methods are described herein for multi-platform interoperability in digital environments. The present disclosure is configured to receive one or more platforms, wherein the one or more platforms comprise multi-platform virtual reality, augmented reality, and extended reality environments. In some embodiments, receiving includes transferring the platform to a platforms operational layer. In some embodiments, the system may receive a central features repository dashboard, wherein the central features repository dashboard comprises one or more features. In some embodiments, the system may create a generate, integrate, and tailor (GINT) module, wherein the GINT module comprises a feature tailor, a feature integrator, and a feature generator; and aggregate, within the platforms operational layer, the one or more platforms, the central features repository dashboard, and the GINT module.
Systems, computer program products, and methods are described herein for extraction of historical data in workflow automation platform architectures. The present disclosure is configured to introduce an advanced approach to historical data extraction from workflow automation platform architectures. At its core, it employs parallel processing, utilizing a multi-threaded asynchronous tool specifically designed within a workflow automation platform architecture framework. This ensures high performance and scalability, enabling easy extraction of large data volumes within designated system maintenance windows without impinging on system performance.
User authentication and validation for performing transactions may be performed by a validation server of a service provider. For example, when a login request or purchase request is received, the request may be authenticated or validated before permitting the requested transaction. In some arrangements, the validation may be delegated to one or more devices or users external to the service provider. Multiple validation users may be consulted for each transaction request to determine a consensus validation decision. A consensus may be reached based on unanimous responses or based on a specified threshold level (e.g., more than 50% responding positively or negatively). The service provider may use this consensus determination to authorize or reject a transaction request.
SYSTEMS, METHODS, AND APPARATUSES FOR IDENTIFYING UNAUTHORIZED USE OF A USER'S AUTHENTICATION CREDENTIALS TO AN ELECTRONIC NETWORK BASED ON NON-PUBLIC DATA ACCESS
Systems, computer program products, and methods are described herein for identifying unauthorized use of a user's authentication credentials to an electronic network based on non-public data access. The present invention is configured to receive a verified access attempt at a first time for a user account; receive an unverified access attempt at a second time for the user account; determine the unverified access attempt is a credential sharing event for the user account; receive unverified account access logs associated with the unverified access attempt, the unverified account access logs comprising access to non-public data; and generate an unverified data access interface component to configure a graphical user interface of a device associated with a manager of the system.
A system is provided for electronic data artifact testing using a hybrid centralized-decentralized computing platform. In particular, the system may comprise an artifact testing platform that may be accessed by users and computing devices within a network. Users may upload a data artifact to the artifact testing platform to be validated by the system. The system may then use a number of different validators (e.g., artificial intelligence-based modules) that may read the data artifact and/or the associated metadata and generate a confidence level based on the characteristics of the data artifact. The confidence levels from each validator may be aggregated to generate a final trust score for the data artifact. If the final trust score is below a first threshold, blocking the user computing device from opening the electronic file and if the final trust score is below a second threshold, performing network segmentation of the user computing device.
A method for session-sharing between an electronic interactive session hosted at a first device and a session hosted at a second device is provided. The second device includes a display arrangement to input confidential information to the second device absent visual trespass. The method also includes establishing communication between a common data storage device, the first device and the second device, transferring user session initiation information to the common data storage device and receiving a user command. The user command locks the first user session at the first device, sends an instruction to the first device to mask a display associated with the first user session, maintains the session initiation information entered at the first device in the database and creates a second user session. The second user session invokes the information from the first device in order to support a confidential data input session at the second device.
Arrangements for steganography-based security document access control are provided. In some examples, a security policy for a document may be generated. The security policy may include identification of one or more users authorized to access the document and one or more response actions to execute upon violation of the security policy. The generated security policy may be embedded in the document using steganography. Accordingly, transmission of the document may include transmission of the security policy with the document. The document may be transmitted to a destination node. A user at the destination node may request access to the document. In response to the request, the security policy embedded in the document may be executed to confirm whether the user is an authorized user. If the user is authorized, access to the document may be enabled. If the user is not authorized, the one or more response actions may be executed.
Systems, methods, and computer program products are provided herein for data security model modification and anomaly detection. An example method includes receiving a model input associated with one or more data entries of a data security model and accessing the data security model. The data security model includes a plurality of data objects including one or more data entries where each data object defines an associated model level indicative of the hierarchical position of the data object within the data security model and one or more links between the data objects that define data object interdependency parameters. The example method further includes determining one or more data objects of the data security model implicated by the model input and modifying one or more data entries of the one or more implicated data objects of the data security model in response to the model input.
A computing platform may train, using smart contract and file type information, a homomorphic encryption model, which may configure the homomorphic encryption model to identify, for a given input file, a corresponding smart contract defining a corresponding set of parameters, included in the given input file, for display. The computing platform may receive an unencrypted file, and may identify, by inputting the unencrypted file into the homomorphic encryption model, a smart contract defining one or more parameters for display. The computing platform may encrypt, using homomorphic encryption, the unencrypted file to produce an encrypted file, and may store the encrypted file. The computing platform may receive, via an application programming interface (API) at a user device, a request to access the encrypted file. The computing platform may send, based on the smart contract and for display at the user device via the API, the parameters for display.
Systems, computer program products, and methods are described herein for client onboarding and exposure detection using large language models (LLMs) for computational efficiency. The present disclosure is configured to receive interaction data associated with a first user and a second user, wherein the interaction data is associated with an onboarding process for the second user; determine, using a behavioral analysis large language model (LLM) module, an interaction response pattern of the second user from the interaction data; determine interaction response times of the second user from the interaction data; compare the interaction response pattern and the interaction response times with past interactions known to be associated with misappropriate activity; determine a likelihood associated with whether the second user is associated with misappropriate activity based on at least the comparison; and execute a mitigation action in an instance in which the likelihood meets a misappropriate threshold.
A system for detecting tampering of an item during transit from a source to a destination. The system includes a processor which receives a plurality of measurements of the environment surrounding the item during transit and detects at least one anomaly in the plurality of measurements. When the at least one anomaly is detected, it is compared with the expected measurement at the location and/or time and if the comparison shows a degree of difference that is greater than a predetermined threshold that indicates the item may have been tampered with during transit, the system and method performs an action to disable the item.
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
G08B 13/189 - Déclenchement influencé par la chaleur, la lumière, ou les radiations de longueur d'onde plus courteDéclenchement par introduction de sources de chaleur, de lumière, ou de radiations de longueur d'onde plus courte utilisant des systèmes détecteurs de radiations passifs
57.
System and method to detect device tampering during transit using a geolocation sensor
A system and method for detecting tampering of an item during transit from a source to a destination. The system includes a processor which receives a plurality of measurements of the position of the item during transit and detects at least one anomaly in the plurality of measurements. When the at least one anomaly is detected, it is compared with the expected location of the item at that time and if the comparison shows a degree of difference that is greater than a predetermined threshold that indicates the item may have been diverted and tampered with during transit, the system and method performs an action to disable the item.
A system includes a memory and a processor that validates an interaction between an initiating and a receiving device. An encrypted request is received to perform the interaction and the processor extracts an initiating device identification, a receiving device identification, and one or more numerical values associated with the interaction. Using this extracted information, the processor produces a verification key by applying a hash function and a verification checksum value using a checksum function. The verification key and verification checksum value are then compared with an authentication key and authentication checksum value that were produced in a same manner prior to the interaction being initiated. If it is determined that either the verification key and the authentication key do not have the same value, or verification checksum value and authentication checksum value do not have the same value, then the interaction is reversed.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
59.
System and method for machine-to-machine re-imaging
An error message is received from a first computing node indicating a malfunction associated with the first computing node. Based on a first error code received in the error message, a first software program is determined that is to be installed at the first computing node to resolve the malfunction. A geographically nearest second computing node to the first computing node is determined that includes the first software program. The second computing node is instructed to transmit the first software program to the first computing node. The second computing node transmits the first software program to the first computing node. The first computing node receives and installs the first software program at the first computing node.
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p. ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p. ex. contrôle de parité, exclusion des 9 ou des 11
60.
System and Method for Managing Interactions on a Blockchain Network
A system is configured to perform an interaction between a first user and a second user. The system comprises memory operable to store a data log comprising information associated with the interaction and a hold duration. The system comprises a processor operably coupled to the memory and a blockchain network. The processor is configured to receive a request from a first user device to record the interaction on the blockchain network, and store information associated with the interaction in a data log. The processor is configured to determine whether a cancel request is received. If received, the processor is configured to cancel the request to record the interaction on the blockchain network. If not received, the processor is configured to hold the request to record the interaction on the blockchain network for the hold duration, and subsequently record the interaction on the blockchain network.
A device for performing a secured operation is disclosed. The device is embedded with a predefined data item and verification information. The verification information is uniquely associated with the user of the device. The verification information is linked to the identity of the user. The verification information is configured to be extracted in conjunction with the secured operation being performed. The secured operation is performed in response to the verification information being verified. A system and method for performing the secured operation are also disclosed.
A request is transmitted to a second computing node of a second blockchain network to perform a data interaction between a first computing node of a first blockchain network and the second computing node. Upon receiving an acknowledgement of the request, a first smart contract, an encrypted first network address and a first authentication code is generated. The first smart contract is encrypted using the first authentication code to generate an encrypted first smart contract. The encrypted first smart contract, the encrypted first network address and the first authentication code is transmitted to the second computing node. A digital signature is received indicating an approval of the first smart contract. Thereafter, data objects are transmitted to the second computing node as agreed in the first smart contract.
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
63.
System and method for alternative interactions using optical absorption spectroscopy
A mobile device performs an alternative interaction with an entity device using optical absorption spectroscopy, such as when a traditional network connection is unavailable between the mobile device and the entity device.
A session-sharing system smoothly toggles between a first device session and a pre-registered second device session. The second computing device enables input confidential information absent visual trespass. The second device is pre-registered with a private key for unlocking a public key. A common data storage device establishes electronic communication between the first and second computing devices by invoking trigger information incorporating a public key from the first computing device. The second computing device executes the trigger information by decoding the public key. The first computing device receives the user session initiation information and then transfers it to the common data storage device. The second computing device locks the first user session, masks a display associated with the first user session, maintains the session initiation information and creates a second user session invoking the information from the first computing device to support confidential data input at the second computing device.
G06F 21/84 - Protection des dispositifs de saisie, d’affichage de données ou d’interconnexion dispositifs d’affichage, p. ex. écrans ou moniteurs
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
65.
GAMIFICATION OF TRAINING FOR PHISHING PREVENTION IN METAVERSE
A system, computer program product, and method for training users in phishing prevention may challenge a user with gamified user-specific phishing attacks for a user to encounter in a temporal pattern. Phishing data, including data relating to phishing techniques and actual and non-actual (fake) phishing attacks, may be generated or obtained and input to the training engine. User-related data, including user information, one or more social engineering vectors, or organization information relating to an organization, may be obtained and digitally manipulated. A sequential cross model training engine may process the phishing data and digitally manipulate the user-related data to generate training activities that include test phishing attacks. A gamification engine may generate gamified user-specific testing that includes two or more of the test phishing attacks in a sequence in real time. The test phishing attacks, which may be in a non-question format, may target the user in an XR environment.
A computing platform may receive an event processing request. The computing platform may identify, by inputting first communication parameters of the event processing request into a secure communication model, communication validation information for the event processing request. The computing platform may embed, using one or more tonal bits of an audio communication corresponding to the event processing request, the first communication validation information, wherein embedding the first communication validation information generates a secure event communication. The computing platform may send the secure event communication to a recipient user device, where the recipient user device may be configured to verify the secure event communication based on the first communication validation information.
Systems, computer program products, and methods are described herein for a system for mapping and executing usage of multiple source elements for completion of a resource request. The present disclosure is configured to receive source element data related to at least two source elements, establish resource request parameters, determine an execution source element, and execute a resource transfer in response to the resource request using the execution source element.
Aspects related to an amalgamation platform providing concealed detection of code-passing using steganography are provided. An amalgamation platform may train a scoring engine to generate suspicion scores for code snippets and an amalgamation engine to generate execution scenarios for the code snippets. The platform may embed code in base code of a network using steganography. The platform may use the steganographic code to detect transmission of a code snippet. The platform may generate a suspicion score for the code snippet. The platform may update the scoring engine based on identifying the suspicion score satisfies a threshold. The platform may generate execution scenarios for the code snippet. The platform may determine a match between an execution scenario and a malicious code scenario. The platform may identify the code snippet as malicious and update the amalgamation engine based on the match. The platform may initiate security actions based on the match.
G06F 21/56 - Détection ou gestion de programmes malveillants, p. ex. dispositions anti-virus
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
69.
INTELLIGENT METHOD FOR REAL TIME CACHE UPDATES LEVERAGING DISTRIBUTED LEDGER TECHNOLOGY WITH NON-FUNGIBLE TOKEN (NFT) TIED SYSTEM OF RECORD (SOR) UPDATE INDICATORS
Aspects of the disclosure relate to using machine learning models to performing real-time cache updates. A computing system may receive a request to update an unreferenced object of a user interface of an application. A block may be generated in a blockchain stored in a second cache tier. The block may comprise a non-fungible token (NFT) based on the unreferenced object and may indicate that the unreferenced object is not authorized to indicate a system of record update. Based on the request to update the unreferenced object meeting one or more criteria, a block comprising an NFT that is referenced by the unreferenced object may be generated in a first cache tier. A block indicating that the NFT is referenced by the unreferenced object may be generated in a first cache tier and the unreferenced object may be updated in the user interface of the application.
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
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
70.
SYSTEM AND METHOD FOR GENERATING DATA MODELS SECURE FROM MALFEASANT MANIPULATION FOR USE IN PREDICTIVE MODELING
Embodiments of the present invention provide a system for generating data models secure from malfeasant manipulation for use in predictive modeling. The system is configured for retrieving training data associated with predictive modeling from a data source, processing the training data retrieved from the data source, transmitting the training data to a local linear model to generate a predictive output, retrieving historical data from the data source, transmitting the predictive output from the local linear model and the historical data retrieved from the data source to a Huber loss estimator module, validating, via the Huber loss estimator module, the predictive output received from the local linear model based on the historical data retrieved from the data source, and determining, via the Huber loss estimator module, if the training data has been manipulated by a malfeasant actor based on validating the one or more data points associated with the predictive output.
Systems and methods for confidential database surgical search and access-less retrieval using a hybrid-computing-powered system with multi-thread processing are provided. The systems and methods may include a quantum processor and a classical processor. The systems and methods may include requesting data elements pertinent to reports. The systems and methods may include authenticating requests and creating classical request strings via a classical processor. The systems and methods may include interfacing classical request strings with a quantum processor. The systems and methods may include running Grover's searches in parallel over the request strings. The systems and methods may include fetching data from smart contracts within ledgers and sub-ledgers within a blockchain. The systems and methods may include pulling dynamic market data through a legacy transformation platform including dynamically derived data values and a machine learning model (MLM).
G06N 10/80 - Programmation quantique, p. ex. interfaces, langages ou boîtes à outils de développement logiciel pour la création ou la manipulation de programmes capables de fonctionner sur des ordinateurs quantiquesPlate-formes pour la simulation ou l’accès aux ordinateurs quantiques, p. ex. informatique quantique en nuage
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
72.
SYSTEMS AND METHODS FOR SECURING AND EMULATING OF COMPUTING SYSTEM CONFIGURATIONS
Systems, computer program products, and methods are described herein for securing and emulating computing system configurations. The present disclosure is configured to identify at least one potential configuration for at least one system component; generate at least one configuration delta for the at least one potential configuration; apply the at least one configuration delta to a configuration delta processing engine; generate, by the configuration delta processing engine, at least one configuration delta processing engine output; apply the at least one configuration delta processing engine output to a configuration emulator engine; output, by the configuration emulator engine, at least one configuration simulation; apply the at least one configuration simulation to a configuration management component, wherein the configuration management component comprises a component configuration distributed ledger; and update the component configuration distributed ledger with the at least one configuration simulation.
The present disclosure details systems and methods for homomorphic encryption-based data caching. This technology detects transaction patterns via a monitoring module that liaises with both a payment system and an entity system. Prior to its processing, transaction data is encrypted with a homomorphic encryption module. A dynamic interface, aligned with a local point-of-sale (POS) cache, prioritizes data based on current transaction metrics. If a recipient server is busy, the transaction data is rerouted, stored in the POS's local cache, and queued. The transaction's success is gauged against a predefined cut-off time. Unsuccessful transactions within this window are slated for batch processing, yet resource processing proceeds while awaiting this batch processing.
Arrangements for a change prediction model using quantum neural networks are provided. A platform may train a quantum change prediction model. The platform may receive and process an event processing request and one or more change instructions. The platform may determine whether a quantity of change instructions associated with the event processing request satisfies a threshold. Based on determining that the quantity of change instructions associated with the event processing request satisfies a threshold, the platform may generate a probability score indicating a likelihood that change instructions corresponding to the event processing request are awaiting identification. Based on determining that the probability score satisfies a threshold, the platform may generate a set of predicted change instructions for the event processing request using the model. The platform may update the model based on the set of predicted change instructions and the probability score. The platform may cause the event processing request to be processed based on the set of predicted change instructions.
An intelligent technical procedure to merge two or more application programming interfaces (APIs) leveraging generative AI is disclosed. API metadata is extracted from two or more APIs (e.g., name of API, endpoints, request/response formats (JSON or XLM), authentication mechanism (API keys, OAuth, or JWT tokens), rate limits, error codes, error messages, version scheme and API documentation etc.) to formulate and generate new API based on user prompt. Using Abstract Syntax tree (AST) advance deep learning generative AI algorithms like Generative pre-trained transformer (GPT) or the like, the method can merge and construct new API based on user's requirement prompt. Method leverages smart contracts to test new generated API and deploy API in desired environment based on blockchain consent protocol to manage API.
Remote access to secured containers is provided by a user interface apparatus having an associated receptacle for receiving physical items delivered from and to the remote secured container. Delivery of the physical items to and from the user interface device's receptacle and the secure container may be accomplished by a robotic mechanism or the like. The user of the remote secured container access system pre-registers, such that presentation of the user credentials at the user interface apparatus provides the user options for receiving items for the secured container and delivering items. Moreover, the user credentials are associated with a secure container identifier and access credentials for gaining access to the secured area and/or the secured container, such that presentation of the user credentials provides identification of the secure container and access to the secured area and/or the secured container.
G07C 9/00 - Enregistrement de l’entrée ou de la sortie d'une entité isolée
B65G 1/137 - Dispositifs d'emmagasinage mécaniques avec des aménagements ou des moyens de commande automatique pour choisir les objets qui doivent être enlevés
G07C 9/32 - Enregistrement de l’entrée ou de la sortie d'une entité isolée ne comportant pas l’utilisation d’un laissez-passer combiné à une vérification d’identité
77.
Decision Making Using Integrated Machine Learning Models and Knowledge Graphs
Aspects of the disclosure relate to machine learning models and knowledge graphs. A computing platform may receive event processing data. Using a machine learning mode, the computing platform may identify k nearest data points corresponding to the event processing data. Using a knowledge graph, the computing platform may identify k nearest data nodes corresponding to the event processing data. The computing platform may generate first weighted relative distances between the event processing data and the k nearest data points, and second weighted relative distances between the event processing data and the k nearest data nodes. Based on the weighted relative distances, the computing platform may identify a data cluster for the event processing data. The computing platform may send, based on the identified data cluster, event processing information and one or more commands directing an enterprise computing device to display the event processing information.
A method includes intercepting requests. The requests are analyzed to identify authenticated requests. Remaining requests are identified as suspicious requests. The suspicious requests are grouped into request groups based on respective geolocation information. A first rate of requests is determined for a first request group. In response to determining that the first rate of requests is less than or equal to a request rate threshold, parameters of a first suspicious request of the first request group are analyzed to determining values of the parameters. In response to determining that the values of the parameters are not within respective acceptable parameter value ranges, the first suspicious request is analyzed using a neural network to identify if the first suspicious request is legitimate or malicious. In response to identifying that the first suspicious request is malicious, a first notification indicating that the first suspicious request is identified as malicious is send.
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
79.
System and method for dynamically merging geofencing rules and messages
A method includes monitoring a first geographic area and a second geographic area. In response to determining that a portion of the first geographic area overlaps with a portion of the second geographic area, an overlapping geographic area is defined. A merged rule set for the overlapping geographic area is generated by merging a first rule set associated with the first geographic area and a second rule set associated with the second geographic area. In response to determining that a user device is located within the overlapping geographic area, a merged alert is generated based on the merged rule set. The merged alert includes merged information of a first alert associated with the first rule set and a second alert associated with the second rule set. A message with the merged alert is sent to the user device.
A system receives an image from a camera, where the image shows a physical device. The system, via deep learning object detection algorithm, determines the identity of the physical device. The system generates a virtual device in a virtual environment, where the virtual device is a virtual representation of the physical device. The system receives a user request that indicates the virtual device is requested to perform an operation. In response, the system establishes a communication path to the physical device and communicates a control signal to the physical device that causes the physical device to perform the operation.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
81.
System and Method for Verifying User Interactions in an Extended Reality Environment
A method includes rendering, on displays of an extended reality (XR) device, an XR environment, detecting a sequence of user interactions with an XR application, and identifying, based on the sequence of user interactions with the XR application and the user identification, a historical user interaction data associated with a user. The method further includes generating a first trust token based on the identified historical user interaction data, and receiving an interaction to finalize execution of the sequence of user interactions. In response, the method includes accessing a second trust token associated with the XR application, comparing the first trust token with the second trust token, validating the second trust token based on the comparison, validating each user interaction of the sequence of user interactions based on the identified historical user interaction data, and finalizing execution of the sequence of user interactions in response to the validations.
G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
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
82.
System and Method for Generating and Securing a User-Specific Application in an Extended Reality Environment
A method includes rendering, on displays of an extended reality (XR) device, an XR environment, and detecting, based on sensor data obtained from sensors of the XR device, a device capability associated with the XR device and one or more environmental conditions associated with the XR environment. The method further includes receiving a request corresponding to one or more user interactions with an XR application. In response to receiving the request, the method includes generating, based the device capability and the environmental conditions, a dynamic digital profile to be associated with the user, in which the dynamic digital profile is dynamically generated to be responsive to one or more input modalities associated with the request, and render, on the displays, the dynamic digital profile. The rendered dynamic digital profile includes a set of elements responsive to the one or more input modalities of the request.
A method includes intercepting requests, which are analyzed to identify authenticated and suspicious requests. The suspicious requests are grouped into request groups based on respective geolocation information. A rate of requests is determined for a request group. In response to determining that the rate of requests is less than or equal to a request rate threshold, parameters of a suspicious request of the request group are analyzed to determining values of the parameters. In response to determining that the value of the parameters do not match with respective malicious parameter values stored in a block list, the suspicious request is analyzed using a neural network to identify if the suspicious request is legitimate or malicious. In response to identifying that the suspicious request is malicious, a notification indicating that the suspicious request is identified as malicious is sent, and the values of the parameters are added to the block list.
A system accesses data of a failed interaction with a target system from a queue and determines whether the failed interaction is a data failure or a system failure. For a data failure, the system determines a category and whether it can be fixed. If it can be fixed, the system updates the data and reprocesses the failed interaction based on the updated data. If it cannot be fixed, the system deletes the data from the queue and notifies the target system the category of the data failure. For a system failure, the system identifies a system trend of the target system and determines whether it can be fixed. If it can be fixed, the system determines a reprocessing schedule and reprocesses the failed interaction accordingly. If it cannot be fixed, the system deletes the data from the queue and notifies the target system of the system trend.
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 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
85.
System and method for identifying anomalous network sessions in a network environment
A system for identifying one or more anomalous network sessions in a network environment includes a memory and a processor coupled to the memory. The processor collects network traffic data based on a plurality of network sessions between a source and a destination in the network environment. The processor parses the network traffic data to identify a plurality of parameters associated with the network traffic data at different network layers. The processor clusters the network traffic data into baseline network traffic data based on one or more specific parameters of the plurality of parameters. The processor identifies unknown network traffic based upon the clustered network traffic data and analyzes the unknown network traffic with respect to the baseline network traffic data to identify the one or more anomalous network sessions. The processor determines and performs one or more mitigation actions for the identified one or more anomalous network sessions.
G06F 18/2321 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p. ex. modélisation des fonctions de densité de probabilité
86.
System and method to integrate microservices in Interactive Voice Response (IVR) operations
An apparatus may comprise a memory communicatively coupled to a processor. The processor may be configured to receive a request to perform multiple data processing operations and determine multiple sub-dialogues corresponding to the request. The sub-dialogues are part of a plurality of IVR operations. The processor may be further configured to route the request to a microservice of the microservices based at least in part upon the sub-dialogues. The microservice may be configured to fulfill the request. The processor may generate a response to the request associated with the microservice, update publishing commands in accordance with one or more rules and policies in response to generating the response, and publish the first microservice. The publishing commands associated with the microservice may be updated in isolation from the rest of the microservices.
Aspects of the disclosure relate to strategizing distributed systems using quantum simulation. A quantum simulation platform may train a quantum simulation model (QSM) and an encoding model. The platform may generate a digital twin of a distributed software system (DSS). The platform may generate a directed acyclic graph (DAG) based on source code for updating the DSS. The platform may generate encoded vectors using the DAG and the encoding model. The platform may generate a source code matrix based on generating distribution assessments for the encoded vectors. The platform may generate a configuration matrix based on generating change vectors using the digital twin. The platform may generate execution scenarios and optimization scores using the QSM, based on inputting the matrices. The platform may identify an optimal execution scenario. The platform may cause one or more updates the DSS based on the optimal execution scenario.
Systems, computer program products, and methods are described herein for implementing a mixed reality apparatus to automatically and dynamically generate output based on source code. The present disclosure is configured to identify at least one source code statement; train the source code output machine learning model with the at least one source code statement; generate at least one input data for the at least one source code statement, the at least one input data is associated with an at least one expected output data; apply the at least one input data to the source code output machine learning model; output the at least one sample output data; transmit the at least one sample output data to a mixed reality apparatus; and compare the at least one sample output data and the at least one expected output data and determine whether the at least one source code statement is valid.
Arrangements for a change prediction model using a quantum neural network are provided. A platform may train a quantum change schema model. The platform may receive and process an event processing request and one or more change instructions. The platform may generate a change schema for the event processing request using the model and based on the one or more change instructions. The platform may cause processing of the change schema. The platform may update the model based on receiving results of processing the change schema. The platform may cause the event processing request to be processed based on the change schema. The platform may further update the model based on modified change instructions received as a result of processing the event processing request.
Systems, computer program products, and methods are described herein for intelligent workflow management in robotic process automation (RPA). The present disclosure comprises a workflow replication subsystem configured to replicate a sequence of actions executed by an RPA bot in an application server; a fog computing subsystem operatively coupled to the workflow replication subsystem, wherein the fog computing subsystem is configured to extract metadata associated with execution of the sequence of actions; and an anomaly resolution subsystem operatively coupled to the fog computing subsystem and the workflow replication subsystem, wherein the anomaly resolution subsystem is configured to troubleshoot instances of interruptions in the execution of the sequence of actions, wherein the instances of interruptions comprise at least potential failures in at least one action yet to be executed by the RPA bot.
Intelligent autonomous software (i.e., a “bot”) configured to compile and present resource advancement requestor-specific dashboards that summarize the results of analysis of resource advancement data related to the resource advancement request/requestor. In compiling a dashboard presentation for a specific resource advancement requestor, the intelligent autonomous software executes a set of predetermined queries directed to a database that stores the results of the data analysis. In response to receiving the responses to the queries, the intelligent autonomous software is configured to identify data omissions/anomalies in the data that will prevent approval of the resource advancement request and identify, and in some instances generate, corrective action(s) that will rectify the data omissions/anomalies. Subsequently, a resource advancement requestor-specific dashboard presentation is generated and communicated to the user that (i) summarizes the data responsive to the predetermined queries, and (ii) highlights the data omissions/anomalies and the corrective actions necessary to rectify the data omissions/anomalies.
G06N 3/006 - Vie artificielle, c.-à-d. agencements informatiques simulant la vie fondés sur des formes de vie individuelles ou collectives simulées et virtuelles, p. ex. simulations sociales ou optimisation par essaims particulaires [PSO]
92.
SYSTEM AND METHOD FOR MACHINE LEARNING-DRIVEN DATA RECORD RETRIEVAL VIA STOCHASTIC EXPANSION DATA QUERYING
Systems, computer program products, and methods are described herein for machine learning-driven data record retrieval via stochastic expansion data querying. Data records and a query statement are received. Using a weighting model, a data vector for each of the data records and a query vector for the query statement are generated. A first similarity score for each data vector is determined. Rankings for the data records are generated. Based on the rankings, a grouping of data records is selected. Test vectors centered from the query vector are then generated stochastically. A second similarity score for each of the test vectors is determined. A subsequent query vector is determined based on a highest second similarity score. If metrics do not satisfy a predetermined stopping criteria, subsequent test vectors are generated stochastically. Ranked data records are then provided to a large language model.
In conventional networked computing systems, stream-processing software is utilized to handle real-time data feeds. For example, a stream-processing software may sort incoming data feeds into data logs, which are then consumed by various application servers within the computing system. However, this consumption process is susceptible to failure as application servers often fail to consume a full payload of data comprising a particular message. As such, a need exists for a streaming architecture with improved fault tolerance. The system provided herein solves the problem via a reliable streaming process, which regularly generates partitions within a series of data lakes. As streaming data is received, the payloads are synced into the different data lakes based on metadata associated with the streaming data. The system can then perform individual quality checks on each partition of data, enabling the system to continuously monitor data quality over time.
G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p. ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
H04L 65/60 - Diffusion en flux de paquets multimédias
94.
MULTI-COMPUTER SYSTEM FOR PERFORMING VULNERABILITY ANALYSIS AND ALERT GENERATION
Arrangements for providing software vulnerability analysis and monitoring are provided. In some aspects, software bill of materials (SBOM) data may be received and software attributes may be extracted from the SBOM data. Author data may be received and analyzed using natural language processing and/or machine learning to identify author attributes. Current event or vulnerability data may be received. In some examples, one or more machine learning models may be executed to determine a confidence score associated with the software being analyzed. For instance, software attributes, author attributes, and current event data may be used as inputs in the machine learning model and a confidence score may be output. Based on the confidence score, one or more alerts may be generated and transmitted to one or more enterprise organization computing devices.
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
A network environment scanning engine may monitor electronic communications received via an external computing network and by an enterprise computing system. The network environment canning engine after receipt of an electronic message, analyze the electronic message to identify, by a network environment scanning engine using a machine learning algorithm, executable code for execution by a processor of computing device addressed as a recipient of the message. The network environment scanning engine further analyzes, using a machine-learning based algorithm in a virtual security environment, the executable code to identify whether the executable code comprises one or more environment variables. Based on the analysis of the executable code, the network environment scanning engine either triggers, based on identification of the one or more environment variables and by an electronic messaging system, an alert sent via a communication network or releases the electronic message for delivery to the recipient computing device.
A system for updating a software code executes a current version of the software code on a web application. The system receives a request message to update the current version of the software code to a new version of the software code. The system determines whether the software code is still being executed on the web application. In response to determining that the software code is still being executed on the web application, the system identifies a subset of portions of the software code that have not yet been executed, executes an update instruction to cause the subset of portions of the software code to be updated, and moves the updated subset of portions of the software code from a first memory block to a second memory block.
A system for addressing a software code update failure receives a request message to update a current version of a software code to a new version of the software code. The system executes an update instruction to cause at least a portion of the software code to be updated. The system records a log file that comprises information about an execution of the new version of the software code and captures a video recording that shows a screen on a computing device on which the new version of the software code is executed. The system detects an error message and in response to the error message, rolls back the new version of the software code to the current version, communicates an alert message, receives an updated configuration file, and re-executes the update instruction configured with the updated configuration file.
A computing platform may generate a digital watermark configured to verify an identity of an initiator of a communication session. The computing platform may send, to a first user device, a digital watermark signal, where the digital watermark signal indicates: a validated digital watermark comprising the digital watermark, and a first frequency at which the digital watermark is embedded. The computing platform may embed, into a request to initiate a communication session, the digital watermark. The computing platform may send, to the first user device, the request to initiate the communication session, where the first user device may be configured to: 1) identify, based on the first frequency, the digital watermark, 2) compare the digital watermark to the validated digital watermark, and 3) based on identifying that the digital watermark matches the validated digital watermark, output an authenticated communication session notification.
Systems, computer program products, and methods are described herein for combinatorial data outlier detection via database query statement generation. A table comprising rows and columns is received, wherein each column comprises records and a corresponding data element. A datatype to be assigned to each data element is determined, based on each column and using a first machine learning model. Conditions are generated for columns corresponding to each data element. The conditions are combined into a predetermined number of condition combinations, wherein the condition combinations comprise combinatorial sequencing of the conditions. A query statement is generated for each of the condition combinations. The table in queried with each query statement to determine query results. A data element quantity and a record quantity in the query results are determined for each query statement.
Arrangements for multi-channel communication validation are provided. In some examples, an indication of initiation of a communication session may be received. The communication session may be initiated by a first party via a first communication channel. In response to the indication, one or more validation actions may be generated and sent to a user device associated with a second party or recipient of the communication session via a second, different communication channel. The second party may acknowledge the validation action and a call completion action may be generated and transmitted to a computing device of the first party. The call completion action may include enabling a connection of the communication session between the first party and the second party if the second party has accepted the call, or may terminate the communication session if the second party has rejected the call.
