The arrangements disclosed herein relate to systems, apparatus, methods, and non-transitory computer readable media for receiving, by a client from a terminal, an External Pre-Shared Key (EPKS) package comprising a transaction key, wherein the transaction key is derived by the terminal using an Initial Key (IK) and a counter, sending, by the client to a server, a first message comprising the TID and the counter, receiving, by the client from the server, a second message in response to the first message, determining, by the client, a session key using the EPKS package, and communicating by the client with the server via a communication session using the session key.
Techniques are described for a complete disaster recovery solution for data streaming platforms that provides regional redundancy using a data replication mode dynamically determined for each application to balance cost and recovery objectives. The techniques determine a data replication mode to use for an application of a plurality of applications that uses a data streaming platform to publish data of the application in a primary management container within a primary region of two or more geographic regions, and replicate the data of the application captured from the primary management container within the primary region to a secondary management container within a secondary region of the two or more geographic regions using the data replication mode determined for the application. The data replication modes may include an inline replication mode and an on-demand replication mode, both of which replicate data asynchronously from a primary region to a secondary region.
The arrangements disclosed herein relate to generating, by a first server, a first seed using a Hash-Based Message Authentication Code (HMAC) based at least in part on a Hash Key (HK), providing, by the first server to each of a first device and a second device, the first seed, providing, by a second server to each of the first device or the second device, a second seed. The second seed is based at least in part on a stream of photons. Each of the first device or the second device generates a Derived Key (DK) based at least in part on the first seed and the second seed. Each of the first device or the second device generates a first key based at least in part on the DK and a first random number generated by a Quantum Random Number Generator (QRNG). The first device encrypts first data using the first key to obtain first ciphertext and provides the first ciphertext to the second device. The second device derives the first key and decrypts the first ciphertext using the first key.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
A computer system and method for migrating on-premise data sources to a cloud platform. The method comprises identifying a source of record from which data is extracted, transformed, and loaded into a load-ready format. Load-ready data is then stored in a network-attached storage with encryption for secure access. Upon detecting the load-ready data via a file polling sensor, a registration directed acyclic graph (DAG) is initiated to register and validate the data within an operational database. A scanning DAG inspects the data for sensitive information, such as personally identifiable information (PII). If sensitive information is detected, a classification DAG identifies specific data elements, and a de-identification DAG encrypts or masks these elements. The de-identified data is then stored in secure cloud storage, where access is enabled within the cloud platform. A monitoring portal provides real-time status updates for the directed acyclic graphs, enhancing oversight of data security processes during migration.
An example computer system for providing countermeasures for a ransomware attack can include: one or more processors; and non-transitory computer-readable storage media encoding instructions which, when executed by the one or more processors, causes the computer system to generate a key by to: create a salt using artificial intelligence; form a data section by the salt and an original key; and form a dummy section to fill out a length of the key.
Systems and techniques may be used to perform multi-capture for remote deposit via video. For example, a technique may include capturing a first video of a first side and a second video of the second side of each of a plurality of checks, and extracting a first set of respective individual images of the first side and the second side of each check of the plurality of checks. The technique may include comparing geometrical features of the first side of each of the plurality of checks to geometrical features of the second side of each of the plurality of checks, and based on the comparison, selecting an image from the first set of respective individual images that corresponds to an image from the second set of respective individual images to form a pair of images.
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
7.
TOKENIZED MODEL TRAINING USING TERM FREQUENCY INVERSE DOCUMENT FREQUENCY
Systems and techniques may generally be used for predicting customer complaints in electronic communications. An example technique may include receiving a plurality of electronic mail messages, preprocessing the plurality of electronic mail messages to create structured text data of each message of the plurality of electronic mail messages, and tokenizing the structured text data of each message to generate a set of tokens corresponding to each word in the structured text data of each message. The example technique may include determining a term frequency within each message of respective tokens, determining an inverse document frequency in the structured text data of each token, generating a uniqueness score for each token based on the term frequency and the inverse document frequency, and training a machine learning model to predict whether an electronic mail message includes a customer complaint using the uniqueness score.
Systems and techniques may generally be used for modifying quantum entangled bit communication. An example technique may include generating, at a first node in a computing network, a random number using a quantum derived seed as input to a random number generator; modifying a program using the random number while maintaining a function output of the program for a given input; receiving, at the first node from a second node, an input based on the random number; and executing the modified program at the first node using the input to obtain an output consistent with the program in an unmodified state.
An example system for managing identity and access within a federated digital ecosystem includes functionality to store and manage identity data associated with users across federated identity domains, which represent distinct organizational boundaries. The system provides authentication and access control services based on open standards and enforces a unified policy framework for access control, entitlements, and consent management. A marketplace stores and manages reusable, modular micro frontend experiences, enabling their retrieval and reuse across application experiences. The system dynamically generates personalized user experiences by assembling micro frontend experiences based on contextual rules and user preferences, integrating identity data to tailor interactions across channels, including web, mobile, and embedded third-party systems. Communication and synchronization ensure consistent propagation of identity updates, including user attributes, entitlements, and consent settings, across federated domains and user interfaces, enabling secure, adaptive, and scalable operations.
A method includes identifying user activity data and one or more performance indicators of a user, processing the user activity data and the one or more performance indicators using one or more machine learning models to generate a user data structure representing one or more relationships between the processed user activity data and the one or more performance indicators, predicting at least one future activity of the user that will impact the one or more performance indicators, determining an actionable activity to be performed based on the predicted at least one future activity of the user, generating and presenting a graphical user interface (GUI) comprising at least one actionable element and at least one message associated with the actionable activity, and executing the actionable activity responsive to a selection of the at least one actionable element by the user.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
Systems, apparatuses, and methods are disclosed for a quantum computation of an extended weighted sum of hashed function values. An example method includes initializing two sets of qubits. The example method also includes transforming the initial quantum states of the sets of qubits into a quantum state encoding the weighted sum of the hashed function values using a sequence of operators. The sequence of operators comprises a first operator that encodes a distribution of real-valued weights as quantum amplitudes in the quantum state of the first set of qubits, a second operator that prepares an entangled quantum state encoding a real-valued function, a third operator comprising a series of Hadamard gates, and a fourth operator whose conjugate encodes a real-valued hash function. The example method also includes utilizing the quantum state encoding the weighted sum of the hashed function values.
The present disclosure is directed to systems, methods, and non-transitory computer-readable media including storing, by a server, cryptographically protected information related to a bar code, the information configured to be accessible via at least one link to the cryptographically protected information. The server determines that the at least one link is accessed by the bar code being read. The server sends to a receiver device the cryptographically protected information.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
13.
Systems and methods for consent capture via a mobile device
Systems and methods for capturing consent via mobile device are described herein. A computer system associated with an institution receives a request for a consent session from an agent terminal. Responsive to the request, the computer system initiates a consent session and transmits a consent request notification to a mobile device associated with a customer of the institution. Based on the customer's selection of the notification, the computer system receives authentication information associated with the customer from the mobile device. Upon authenticating the consent session, the computer system receives a consent decision from the mobile device. The computer system stores a record of the consent decision in a consent databases. The computer system transmits a customized visit summary to the mobile device, the customized visit summary comprising the record of the consent decision.
A system includes a machine learning model engine and a machine learning model analyzer. The machine learning model engine executes a machine learning model that has been trained with training data and processes scoring data to generate predictions. The machine learning model analyzer evaluates the machine learning model, determines a plurality of drift metrics for the plurality of input variables to compare the distribution of the training data to the distribution of the scoring data, determines an overall drift metric for the combination of the input variables, and generates an alert based on the overall distribution of the training data relative to the overall distribution of the scoring data. The overall drift metric compares an overall distribution of the training data to an overall distribution of the scoring data, where the plurality of input variables are weighted in the overall drift metric in accordance with a plurality of feature importances.
G06F 17/17 - Function evaluation by approximation methods, e.g. interpolation or extrapolation, smoothing or least mean square method
G06F 18/21 - Design or setup of recognition systems or techniquesExtraction of features in feature spaceBlind source separation
G06F 18/2113 - Selection of the most significant subset of features by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
A system for scrubbing contact information is provided. First data for an individual is received from a first source. The first data has content and a first value. Second data for the individual is received from a second source. The second data has the content and a second value different from the first value. Reconciled data is generated by assigning a tag to the first and second data and comparing the first value with the second value. Reconciled data is also generated by changing the first or second value to the other of the first or second value such that values for the first and second data are consistent. The reconciled data is sent to a consent engine for scrubbing. The reconciled data is scrubbed based on the tag. The scrubbed data is then sent to the first and second sources.
A provider computing system includes a processing circuit having a processor coupled to a memory device. The memory device stores instructions thereon that, when executed by the processor, cause the processing circuit to perform operations including retrieving account information of one or more accounts associated with a user, monitoring the account information for real-time updates, and causing a first portion of a user interface to display an overlay on a user device associated with the user. The first portion includes one or more selectable elements indicative of at least a portion of the account information and one or more of the real-time updates. Each selectable element can cause, when selected, a second portion of the user interface to display additional information relating to an account of the one or more accounts associated with the selected selectable element. The first portion can dynamically move across the user interface.
Systems, apparatuses, methods, and computer program products are disclosed for determining a value corresponding to a composite object. Paths are determined using initial values of underlying items of the composite object and random numbers. A DNN is trained by determining a final value for each path based on a final set of items corresponding to the path at the final time, iterating the value backward in time using a non-linear generator function from the final value to an initial value, defining a set of initial values comprising the initial value determined for each path and determining a statistical measure using the set of initial values, and modifying DNN parameters based on the statistical measure. Value information comprising the value for the composite object at one or more times is determined based on output of the DNN. The value information is provided such that a user computing device receives it.
A computing system for imparting security to a data element includes at least one processing circuit. The processing circuit performs operations including receiving the data element; receiving a request to access the data element from a data requestor; tagging the data element with a label regarding the request; determining an expected usage of the data element and storing information regarding the expected usage; providing the data requestor with access to the data element; receiving information regarding an actual usage of the data element; comparing the information regarding the actual usage to the information regarding the expected usage; in response to determining that the actual usage complies with the expected usage, providing a notification regarding a compliance of the actual usage; and in response to determining that the actual usage does not comply with the expected usage, providing a notification regarding non-compliance of the actual usage.
Techniques are described for computer-based determination of significant attributes associated with a time series dataset and generation of technical insights for the time series dataset based on the significant attributes. The disclosed techniques include a computing system configured to obtain time series data of a metric, determine attribute values for a plurality of attributes associated with the time series data of the metric, obtain ranking values for the plurality of attributes, assign an importance value to each respective attribute of the plurality of attributes associated with the time series data of the metric based on an attribute value of the respective attribute and a ranking value of the respective attribute, and generate at least one technical insight for the time series data of the metric based on the respective attribute having a largest importance value of the plurality of attributes associated with the time series data of the metric.
A computer system for machine learning-based prediction is disclosed. The system applies a neural network-based spline transformation to input variables to generate transformed features. The transformed features are processed using a cross network comprising one or more cross layers, each configured to model feature interactions by combining prior layer outputs with learned weight parameters and applying a “cross” (multiplication) transformation with the input features. An output prediction is generated based on the transformed features processed by the cross network. The disclosed approach enables improved modeling of feature interactions while leveraging neural network-based transformations, facilitating enhanced interpretability and computational efficiency in machine learning applications.
Systems and methods for database migration are described. The systems and methods are described as encompassing a series of operations including receiving a message to a first database system where the first database system includes a production service coupled to a first database, and transmitting the message to the production service. The operations include storing the message in a message queue in a second database system including a test service coupled to the second database. The operations include transmitting the message to the test service, and, in response to the message, receiving a test response from the test service. The operations include logging the test response.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
A system for processing a transaction for a flexible credential may be configured to receive, from a payment network, an indication of a payment transaction involving an accountholder of a group payment account, the payment transaction including a payment amount, the flexible credential linked to the group payment account, and the group payment account including a plurality of members; evaluate rules established by the accountholder to determine: a) a set of funding sources to use in the payment transaction, each of the set of funding sources held by a different member of the plurality of members, and b) a respective portion of the payment amount to be allocated to each of the set of funding sources; and complete the payment transaction by initiating separate payment transactions with each of the set of funding sources for the respective portion of the payment amount.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
23.
BOT ACCESS PREVENTION DATA USED FOR COLLECTIVE SUPERVISED LEARNING OF UNSTRUCTURED DATA
Systems and techniques may generally be used for presenting a login challenge and using results of the login challenge as a label for unstructured data. An example technique may include receiving a login request, presenting, in response to receiving the login request, a user interface, the user interface including unstructured data, and receiving, via the user interface, data classification information related to the unstructured data, via the user interface. The example technique may include verifying that the login request was generated by a human using the data classification information, and allowing, in response to verifying that the login request was generated by a human, the login request to proceed. The data classification information may be output as a label of the unstructured data. In some examples, the label or the unstructured data may be used to train a machine learning model.
System, apparatus, and computer program products are disclosed for protected display of a shared visual data object for an audiovisual conference session. In one aspect, a method includes receiving the shared visual data object, wherein the shared visual data object comprises visual data associated with one or more shared user interfaces; determining, using user interface generation circuitry and based on the shared visual data object, one or more protected data values associated with one or more protected data fields; generating, using the user interface generation circuitry, a masked visual data object based on each masked representation and each spatial coordinate set; and causing, using the user interface generation circuitry and/or the communications hardware, the masked visual data object to be displayed using the audiovisual conference session.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
H04L 12/18 - Arrangements for providing special services to substations for broadcast or conference
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
H04L 65/403 - Arrangements for multi-party communication, e.g. for conferences
The present disclosure is directed to systems, methods, and non-transitory computer-readable media including storing, by a server, cryptographically protected information related to a bar code, the information configured to be accessible via at least one link to the cryptographically protected information. The server determines that the at least one link is accessed by the bar code being read. The server sends to a receiver device the cryptographically protected information.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
A system for scrubbing contact information is provided. First data for an individual is received from a first source. The first data has content and a first value. Second data for the individual is received from a second source. The second data has the content and a second value different from the first value. Reconciled data is generated by assigning a tag to the first and second data and comparing the first value with the second value. Reconciled data is also generated by changing the first or second value to the other of the first or second value such that values for the first and second data are consistent. The reconciled data is sent to a consent engine for scrubbing. The reconciled data is scrubbed based on the tag. The scrubbed data is then sent to the first and second sources.
Systems and methods for servicing an ATM may include identifying, by the one or more processors, an error code corresponding to an automated teller machine (ATM); comparing, by the one or more processors, the error code and one or more problems regarding the ATM not resulting in an error code; determining, based on the comparison, a predicted issue affecting the ATM; applying, by the one or more processors as an input, data corresponding to the predicted issue and the error code to a machine learning model to determine one or more actions for responding to the error code corresponding to the ATM; and providing, by the one or more processors, the one or more actions for rendering on a user interface, to facilitate servicing the ATM.
Systems, apparatuses, methods, and computer program products are disclosed for optimizing an item partitioning benefit. An example method includes detecting, by detection circuitry, a user visit event at an establishment that is associated with a user attribute set. The example method further includes determining, by a multimodal engine and based on the user attribute set, a user digital identity wallet comprising one or more user digital identities associated with a benefit set. The example method further includes, identifying, by a selection engine, one or more candidate items, and determining for each candidate item, by the selection engine and using a digital identity selection model, an optimal user digital identity indicative of an optimal item partitioning benefit. The example method further includes generating, by the selection engine and using the digital identity selection model, a candidate item partitioning set, and outputting, by communications hardware, a verification request.
This technical solution can generate, based on a first content object, a NFT including a link with the first content object and compatible with a first control structure that restricts a first output of the first content object to a first remote device, divide, in response to a request to modify the first content object, the first content object into a second content object and a third content object, generate, based on the second content object, a second NFT including a link with the second content object and compatible with a second control structure that restricts a second output of the second content object to the first remote device, and generate, based on the third content object, a third NFT including a link with the third content object and with a third control structure that restricts a third output of the third content object to a second remote device.
Various embodiments described herein relate to systems, methods, and non-transitory computer-readable media structured to perform server-to-device secure data exchange. A device can generate a device access token for an application based on a device identifier and an account identifier for a user account. The device can receive an account restriction applicable to the application and a transaction request from the application. Based on the account restriction, the device can select a function call and transmit, to a computing system and using the function call, the device access token to carry out the transaction request. The computing system can validate the transaction request against the account restriction and transmit an electronic message to the device, which can provide a response to the application based on the electronic message.
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
H04L 67/133 - Protocols for remote procedure calls [RPC]
32.
DATA INSIGHT AND EXPLORATION WITH NATURAL LANGUAGE QUERIES
Certain aspects of the disclosure pertain to natural language data exploration. A computing system may manage a data catalog integrating diverse data sources. To facilitate intelligent exploration of this data, the system can utilize a multi-agent architecture. An orchestration agent can obtain a natural language query, interpret a semantic intent, and determine an execution strategy by selecting and sequencing specialized execution agents. The orchestration agent routes execution parameters to the selected agents and combines their analytical results. Furthermore, prior to user presentation, the orchestration agent can intercept retrieved data and transmit the data to a security agent to evaluate user access rights against real-time security conditions. A formulated response is then output based on this evaluation, enabling secure and orchestrated data insights.
A computer system for a change management intelligent reconciliation platform configured to support the change management process. The computer system includes a task mining agent, an intelligence reconnaissance service, an insight service, and a notification service. The task mining agent is programmed to passively log user actions related to a change request. The intelligence reconnaissance service filters the logged actions and identifies patterns and anomalies in user behavior. The insight service analyzes the differences between the filtered actions and one or more prescribed actions related to the change request, and generates one or more reconciliation insights based on the results of the analysis. The notification service generates one or more notifications regarding the generated reconciliation insights to provides valuable insights into user behavior data and to aid in identifying potential risks or issues during the change implementation process.
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
An example system for minimizing damage to an automated teller machine can include: the automated teller machine; and a base supporting the automated teller machine, the base having a tipping mechanism configured to enable controlled movement of the automated teller machine; wherein the base is configured to be installed within an opening to allow the base of the automated teller machine to move relative to the opening to execute the controlled movement; and wherein the controlled movement is a tipping of the automated teller machine.
G07F 19/00 - Complete banking systemsCoded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
35.
MANAGEMENT OF MULTIPLE DIGITAL IDENTITIES USING A CENTRALIZED DISTRIBUTED LEDGER
Systems, apparatuses, methods, and computer program products are disclosed for digital identity selection. An example method includes detecting a digital identity selection event for a user, wherein the digital identity selection event is associated with an event attribute set comprising one or more event attributes, and an event criteria set comprising one or more event criteria. The example method further includes determining, based on the event attribute set, a master digital identity associated with the user, wherein the master digital identity comprises one or more user digital identities. The example method further includes generating, based on the master digital identity, one or more bespoke digital identities. The example method further includes selecting, using a digital identity selection model, an optimal digital identity, wherein the optimal digital identity satisfies the one or more event criteria of the event criteria set, and outputting the optimal digital identity.
Systems and methods are directed to detecting fraudulent activity based on biometric signatures. A capture component captures data associated with user interactions with a user interface displayed by a computing device. The captured data includes mouse movement. The captured data is converted into an image of the mouse movement. An image encoder encodes the image into an image vector. Subsequently, an analysis system searches a vector database to identify one or more historical image vectors that are similar to the image vector. The vector database comprises a plurality of image vectors corresponding to previously encoded images, whereby at least some of the plurality of image vectors are flagged as indicating fraudulent activity. A result based on the identified historical image vectors is outputted. The result can comprise a risk score for each of the identified historical image vectors that is based in part on a similarity difference measurement.
Systems, apparatuses, methods, and computer program products are disclosed for estimating a crypto-agility score of a network of computing assets. An example method includes receiving a network graph and a set of expert-determined importance weights and selecting a first network node from a set of network nodes. The example method further includes computing an upgrade cost for the first network node based on a set of dependency network nodes and applying an expert-determined importance weight to the upgrade cost for the first network node to determine a weighted upgrade cost for the first network node. The example method further includes adding the weighted upgrade cost for the first network node to a set of weighted upgrade costs and summing, by the graph circuitry, each weighted upgrade cost from the set of weighted full upgrade costs to determine the crypto-agility score for the network of computer assets.
Systems and methods for generating digital dashboards are disclosed. A financial institution system can receive, from an enterprise computing system, a request to generate a dashboard template for an enterprise. The system can retrieve, from applications executing on computing devices of the enterprise, information identifying enterprise activities for inclusion in a dataset corresponding to the enterprise. The system can generate the dashboard template for digital dashboards to be provided to clients of the enterprise by populating fields using the dataset, provide the dashboard template to the enterprise computing system, and accept selections identifying which fields are to be made available to which clients. The system can provide different digital dashboards to different client devices. The system can acquire location information from a GPS-enabled computing device of an enterprise, determine that the device is near a predetermined location of a client device, and provide an indication in a digital dashboard.
Systems, methods, and computer readable media for node-based network access control. A system can include one or more processors to receive a network access request including metadata corresponding with accessing a protected network using a computing device. The one or more processors apply the metadata to a node model to generate a first node. The one or more processors generate a metadata object, generate a control structure, and record the control structure. The one or more processors generate a token including a token identifier, the token corresponding with the metadata object and compatible with the control structure. The one or more processors record the token identifier and receive an output or update request. The one or more processors access, by interfacing with the control structure, the metadata object, determine network access rights or restrictions, and provide or restrict access of the computing device to the protected network.
Various examples are directed to computer-implemented systems and methods for context-based life planning interactions. A method includes receiving information related to events that may implicate estate transfer, and automatically identifying one or more potentially life-threatening events using machine learning based on the information. A casualty score is generated for the one or more potentially life-threatening events and one or more potentially impacted individuals of the one or more potentially life-threatening events are automatically identified using the machine learning. An impact likelihood score is generated for the one or more potentially impacted individuals, and the one or more potentially impacted individuals are categorized into an impact category based on the impact likelihood score. Estate transfer related action items are automatically generated for a financial institution advisor of the one or more potentially impacted individuals based on one or more of the impact likelihood score, the casualty score or the impact category.
Systems, methods, and computer readable media for node-based resource protection. A system can include one or more processors to determine a first node for an encoded object of a resource instrument, generate a metadata object including at least one resource lifecycle indicator, and generate and record a control structure including a link to the metadata object. The one or more processors to generate at least one token compatible with the control structure, record a token identifier, and receive, from a one scanning device or instrument system using the encoded object, an update or output request including the first node. The one or more processors to access the metadata object, identify the private state of the resource instrument based on the at least one resource lifecycle indicator, and transmit, to the at least one scanning device or instrument system, a confirmation or a status alert.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
Systems, apparatuses, methods, and computer program products are disclosed for disclosure validation. A method includes determining an applicability status for digital content indicating whether a required disclosure applies to the digital content, and determining a disclosure inclusion status for the digital content indicating whether the digital content includes a candidate disclosure. The method also includes, in response to determining a disclosure inclusion status that indicates that the digital content includes the candidate disclosure, determining a conformity status for the digital content that indicates whether the candidate disclosure conforms to a set of styling requirements, determining a digital content status for the digital content based on at least one of the applicability status, the disclosure inclusion status, and the conformity status, and causing presentation of the digital content status.
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
Systems, methods, and non-transitory media for managing permissions for accessing and using user data are disclosed. A system can receive, from a user device of a user, location data indicating a physical location of the user device. The system can credit a rewards value to an account of the user based on the location data indicating the physical location of the user device. The system can modify a permission to permit usage of the rewards value in subsequent electronic transactions involving the account based on at least one interaction with one or more graphical user interfaces provided via an application executing on the user device. The system can receive an authorization request for an electronic transaction using the account. The system can apply the rewards value by reducing a value for the electronic transaction based on the rewards value according to the permission.
Systems and techniques for automatic file creation and location selection standardization are described herein. An electronic file storage structure configuration may be received for an application. An electronic file configuration for the application may be received. A configuration prediction machine learning model may be trained using the electronic file storage structure configuration, the electronic file configuration, and application data. User activity data may be obtained for a user activity initiated using the application. The user activity data may be evaluated using the configuration prediction machine learning model to output a predicted file storage structure configuration and a predicted file configuration. A configuration user interface may be generated using the predicted file storage structure configuration and the predicted file configuration. The configuration user interface may be presented to a user.
As the number of applications developed by the organization increases, the computing resource costs for storing and maintaining applications may also increase significantly. The disclosed content claiming system provides a solution to reducing computing resources necessary to maintain and store content that is no longer needed by allowing users to claim ownership over content and confirm whether the content is still in use. For example, in the disclosed content claiming system, a user initiates the process of content claiming by accessing a user interface associated with a content claiming application, wherein the user interface displays a listing of content currently maintained by the organization. The user may then select unclaimed content objects based one or more preferences and provide attestations regarding ownership and usage. Content claiming helps organization make informed decisions regarding continued storage and maintenance of content.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
Systems and techniques for cloud security posture management are described herein. Cloud configuration data is obtained for a security asset of a cloud computing environment. The cloud configuration data is evaluated by a machine learning processor using a requirements control model to output a probability of a misconfiguration of the security asset. A mitigation action is generated for the security asset based on the probability of the misconfiguration being within a threshold. A cloud security configuration policy is updated for the security asset using the mitigation action and the mitigation action is transmitted to the security asset to modify a cloud configuration of the security asset.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
47.
KEY ESTABLISHMENT AND SECURE COMMUNICATIONS BASED ON SATELLITE-CONNECTED ENTROPY SOURCES
Systems and techniques for secure communications and distribution of random values, provided via satellite communications, are described. These random values are generated from one or more ground-based entropy sources (e.g., quantum random number generators (QRNGs) at terrestrial locations), and optionally combined with values from satellite-based entropy sources (e.g., QRNGs at non-terrestrial locations). An example method includes: receiving a first random value generated by a first QRNG at a terrestrial location; receiving a second random value and a third random value via at least one satellite communication, each additional random value generated by other QRNGs; and generating a cryptographic key based on the first random value, the second random value, and the third random value. The cryptographic key may be produced by a key derivation function that combines the random values, and the cryptographic key may be used to establish a secure communication session.
Systems, apparatuses, methods, and computer program products are disclosed for verifying accuracy of models trained using synthetic data. An example method includes selecting, by data analysis circuitry, an authentic data point set from an authentic dataset. The example method also includes generating, by modeling circuitry and using the authentic data point set, output data of a model having been trained using a synthetic dataset. The example method also includes determining, by model scoring circuitry, an accuracy score for the model based on the output data.
Systems and methods for processing check images using a mobile device are disclosed. A method includes: displaying, on a display screen of the mobile device, an image captured using an image sensor; overlaying a guide on the image on the display screen; determining that the image depicts a check within the guide; responsive to determining that the image depicts the check within the guide, extracting one or more characters corresponding to the check depicted in the image; determining a confidence level for a restricted endorsement in the image, the confidence level based on (i) the one or more characters of the restricted endorsement being within a predetermined area of the image and (ii) the one or more characters of the restricted endorsement forming a predetermined word or phrase; and transmitting, responsive to the confidence level satisfying a predetermined threshold, the image to a check processing computer system.
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
The present disclosure is directed to systems, methods, and non-transitory computer-readable media for generating, by a first node, an encrypted protected message. Generating the encrypted protected message includes generating an obfuscated message by intercalating a second message into the first message, generating a protected message by applying a plurality of data protection mechanisms to the obfuscated message, and generating the encrypted protected message by applying a plurality of confidentiality techniques to the protected message. The first node transmits to a second node the encrypted protected message using a plurality of communication channels.
Systems, apparatuses, methods, and computer program products are disclosed for deriving call intent probability. An example method includes receiving a set of call menu tokens and creating an n-gram from the set of call menu tokens. The example method further includes receiving an intent call log for a candidate call intent, which includes a frequency of the n-gram and a total frequency, and determining, by scoring circuitry, an n-gram intent score based on the frequency of the n-gram and the total frequency of the intent call log. The example method further includes determining a total score for the candidate call intent based on the n-gram intent score, where the total score provides a measure of a probability of the candidate call intent and outputting a ranked list of call intents comprising the total score and the candidate call intent.
Systems and methods for prioritizing fraud cases are disclosed, and include generating a plurality of category queues based on ranking each case of sets of fraud cases, determining an updated priority score for each fraud case based on transaction data and case prioritization data including rules developed using a machine learning model, sorting the plurality of category queues based on the updated priority score, assembling a first group of the fraud cases associated with a first risk level of a first queue in a database, and performing an action on a second group of the fraud cases associated with a second risk level of a second queue, where the machine learning model is retrained based on the transaction data and the case prioritization data is restructured based on the retrained machine learning model.
A system can generate a dependent linkage between a first digital identification (ID) and a second digital ID. The system can classify the first digital ID as a primary digital ID and the second digital ID as a dependent digital ID, where the primary digital ID maintains elevated data access permissions relative to the dependent digital ID. The system can define an expiration trigger for the dependent linkage, where the expiration trigger is responsive to a temporal length of a scheduled event. The system can cause, during the scheduled event, a presentation of a verification message on a computing device associated with the primary digital ID, where the verification message includes data associated with the primary digital ID and data associated with the dependent digital ID and is usable to facilitate a single-scan authentication event.
Systems and methods for structure electronic communications intermediation service including: receiving, from an external resource, a message; filtering the message based on a filtration protocol; identifying a first request within the message; managing a queue for the first request among a plurality of additional requests; identifying a first processing procedure of the first request; processing the first request per a first processing procedure based on an identified configuration of the first request; and transmitting the processed first request.
Systems and methods are disclosed herein for collaborative transactions using a shared interface. An example method includes receiving a first command to begin a transaction and displaying a user interface (UI) element depicting a modifiable parameter. The example method also includes receiving a second command to begin the collaborative transaction and transmitting the first command and an indication of the UI element to a server. The example method also includes displaying a chat interface and a chat UI element depicting the modifiable parameter and receiving, from the server, an indication that the linked account has modified the chat UI element. The example method also includes displaying an updated chat UI element and receiving a third command to finalize the transaction. The example method also includes updating the modifiable parameter based on the updated chat UI element and transmitting the third command to the server.
Systems, apparatuses, methods, and computer program products are disclosed for adjusting institutional interactions with a customer based on user device location data. The example method includes receiving a location routine for a user device and current location of the user device. The example method further includes determining whether a deviation condition for a candidate deviation event type is satisfied based on the current location and the location routine. The example method further includes detecting the occurrence of a deviation event associated with a deviation event type in response to determining that the deviation condition for a candidate deviation event type is satisfied. The example method further includes updating a customer account associated with the user device based on the deviation event type, wherein updating the customer account comprises at least one of (a) applying an account restriction, and (b) modifying customer information within the customer account.
G01S 5/02 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations using radio waves
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
Systems and methods for communicating with a rewards system are described herein. A method includes: establishing, by a provider computing system, an application programming interface to enable communication between the provider computing system and a client application installed on a user device of a user; determining that at least one rewards engagement message presented in the client application was dismissed; transmitting a second rewards engagement message for display in the client application, the second rewards engagement message transmitted based on determining that the at least one rewards engagement message was dismissed; receiving, by the provider computing system and from the client application, an indication of an interaction with the second rewards engagement message; generating a value regarding a rewards account of the user based on the interaction; and assigning redemption points to the rewards account based on the value.
Systems and techniques for flexible credential enabled push notifications are described. A unified payment credential links multiple funding sources through encrypted communication channels. The system determines optimal processing paths between default and alternative paths while preserving transaction state through secure queuing without pre-authorization charges. A rules engine analyzes merchant categories and calculates rewards across funding sources in real-time. Transaction integrity is maintained during source switching through authenticated state transitions and parameter encryption. The system generates secure push notifications about alternative funding options, processes authenticated user responses and preserves transaction states during user interaction. Status updates are synchronized across digital interfaces through protected channels. The implementation enables secure transaction processing while maintaining optimization capabilities through sophisticated rules processing, real-time notifications, and protected state management.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G06Q 30/0207 - Discounts or incentives, e.g. coupons or rebates
Systems and techniques may generally be used for verifying a caller is authentic. An example technique may include receiving an authentication request during an audio call with a caller, playing, during the audio call, a set of sounds, capturing audio received from the caller during the audio call, and processing the audio to generate a voice portion including the voice data and to attempt to generate a background portion including a reverb of the set of sounds. The example technique may include determining whether the background portion including the reverb was generated, and in response to determining that the background portion including the reverb was not generated, outputting an indication denying the authentication request.
H04M 3/22 - Arrangements for supervision, monitoring or testing
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G10L 17/02 - Preprocessing operations, e.g. segment selectionPattern representation or modelling, e.g. based on linear discriminant analysis [LDA] or principal componentsFeature selection or extraction
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G10L 25/69 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for evaluating synthetic or decoded voice signals
H04M 3/42 - Systems providing special services or facilities to subscribers
H04M 9/08 - Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic
60.
SYSTEMS AND METHODS FOR LINKING METAVERSE IDENTITIES
Systems, apparatuses, methods, and computer program products are disclosed for linking a real-world identity and a metaverse identity. An example method includes receiving an indication of user input from a user avatar, the user input comprising a user identification and a set of input parameters, and verifying, by a distributed application engine, authenticity of the input parameters. The example method further includes generating, by cryptographic circuitry, an authentication hash of hash components, the hash components comprising the set of input parameters, and transmitting the authentication hash to an authentication entity. The example method further includes, in response to transmitting the authentication hash to the authentication entity, receiving customer verification data pertaining to a user associated with the user avatar, and generating, by blockchain circuitry and based on the customer verification data, a block on a distributed ledger, wherein the block comprises the set of input parameters.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
A computer system and method for improving call center routing through analysis of customer interactions including obtaining identifying information for a caller upon initiation of a call, identifying the caller as a repeat customer using the identifying information, retrieving historical interaction data associated with the repeat customer from a database, analyzing any combination of customer audio data, customer call log information, or customer feedback, utilizing an artificial intelligence algorithm to determine a current mood indicator of the customer, calculating a customer behavior score for the repeat customer based on the historical interaction data and the current mood indicator of the customer, and matching the repeat customer to a call agent, based on the customer behavior score.
Systems, apparatuses, methods, and computer program products are disclosed for providing secure transaction validation. An example method includes receiving a transaction request from a user device, wherein the transaction request is associated with a user account and the transaction request comprises location data of the user device. The example method further includes determining that a restriction applies to the transaction request for the user account and determining whether the location data corresponds to a trusted location associated with a verified trusted organization using a verified trusted organization repository. The example method further includes modifying the restriction applied to the transaction request in response to determining that the location data corresponds to the trusted location. The example method further includes evaluating whether the transaction request is permissible based on the modified restriction and in response to determining that the transaction request is permissible, validating the transaction request for the user account.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
63.
SYSTEMS AND METHODS FOR TRACKING TECHNICAL ENGAGEMENT OF DIGITAL RESOURCES
Systems, apparatuses, methods, and computer program products are disclosed for monitoring and tracking technical engagements between digital resources. An example method includes deploying a machine learning monitoring application to a computing environment comprising one or more of a computing device or a network channel and detecting an engagement metric associated with a target technology of the computing environment and a user account of the computing environment. The example method further includes generating name-value pair data representative of the engagement metric, the user account, and a timestamp token and generating a technical engagement score representative of a probability of a successful utilization of the target technology by the user account. The example method further includes initializing an actionable instruction set based on a comparison of the technical engagement score to a technical engagement threshold.
A computer system includes at least one processing circuit. The at least one processing circuit includes a processor and instructions stored in non-transitory machine-readable media. The instructions are configured to cause the at least processing circuit to: provide a token to a first third-party system of a first third-party, the token associated with non-payment information; receive a notification from the first third party system that the token has been sent to a second third-party; receive identifying information associated with the second third-party; and determine, based on the identifying information, that the second third-party is authorized to access the non-payment information associated with the token.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06Q 20/34 - Payment architectures, schemes or protocols characterised by the use of specific devices using cards, e.g. integrated circuit [IC] cards or magnetic cards
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
65.
SYSTEMS AND METHODS FOR PAYMENT USING LINKED ASSETS
Systems and methods are disclosed herein for paying by a linked account. An example method includes initiating a transaction comprising a cash value, where the transaction involves a merchant service provider, and retrieving, from a digital wallet, a first data object including transaction details and an indication of a linked account. The example method also includes sending a transaction request including the cash value, an indication of the merchant service provider, and a transaction detail, and receiving a first payment token including an indication of the linked account and approval of the transaction by the linked account. The example method also includes modifying the first payment token to produce a second payment token, transmitting the second payment token to the merchant service provider, receiving a response message generated by the merchant service provider, and causing display of a message indicating the successful transaction.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
A computing system includes a network interface circuit structured to facilitate data transmission over a network, and at least one processing circuit configured to: generate and display a first code including a first unique identifier, the first code being configured to be captured by a user device associated with a user and configured to cause a browser or an application to launch on the user device; generate and display a second code specific to the user device including account information specific to a user account associated with the user and also including a second unique identifier; receive a user confirmation from the user device in response to the second code being captured by the user device, the user confirmation including the first and second unique identifiers; and cause an opening of the user account in response to confirming the first unique identifier corresponds with the account information.
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
67.
SYSTEMS AND METHODS FOR PROVIDING USER PREFERENCES FOR A CONNECTED DEVICE
Systems and methods for providing user preferences for a connected device are disclosed. A system can obtain one or more preferences related to a computing device having one or more adjustable settings. The system can receive a request to update the one or more adjustable settings of the computing device. The request can be transmitted based on a user computing device being paired with the computing device. Responsive to receiving the request, the system can send the one or more preferences to the computing device thereby causing the computing device to adjust at least one of the one or more adjustable settings based on the one or more preferences.
Two-factor authentication code generation devices are described which include accessibility features and/or additional authentication features to ensure an identity of a user.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
69.
Display screen or portion thereof with a transitional graphical user interface
A computer-implemented method includes: determining, by a provider computing system associated with a provider, that a transfer service token of a customer is linked to a first customer account held by another provider; transmitting, by the provider computing system, a prompt to a customer device associated with the customer, the prompt including a selectable option configured to switch the transfer service token from being linked to the first customer account to being linked to a second customer account of the provider; receiving, by the provider computing system, a selection of the selectable option from the customer device; and transmitting, by the provider computing system, a transfer service token switch request to a transfer service computing system, the transfer service token switch request initiating a switch of the transfer service token from being linked to the first customer account to being linked to the second customer account.
Systems and methods for validating payment requests are disclosed. A system can receive, from a user device, a payment request submitted via a payment application or a browser, the payment request including an account number. The system can transmit application programming interface (API) calls to a plurality of computing systems to validate the payment request. The system can receive, from a first computing system, a first response indicating that the account number is associated with an intended beneficiary, and can receive, from a second computing system, a second response indicating at least a name associated with the account number. Based on the first response and the second response, the system can determine a value indicative of a likelihood that the account number is associated with the beneficiary. The system can transmit an alert and receive a request to permit the payment request in lieu of validation.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
A computing system includes a network interface circuit structured to facilitate data transmission over a network, and a processing circuit having one or more processors coupled to non-transitory memory storing instructions that when executed by the one or more processors, cause the processing circuit to: generate and cause a providing of a second code regarding a customer to a customer device associated with the customer; and in response to receiving the second code from the customer device within a predefined parameter of receiving an indication of a capturing of a first code from the customer device, cause an opening of an account for the customer.
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
Techniques described herein involve processes and systems for performing identity verification on a network. In one example, this disclosure describes a method that comprises receiving, by a computing system and from a requesting device, a request to perform an identity verification for a requesting user that is operating the requesting device; outputting, by the computing system and to the requesting device, code information; enabling, by the computing system, the requesting device to display a code derived from the code information; receiving, by the computing system and from a verification device, an image of another device; and determining, by the computing system and based on the image of the other device, whether the other device is the requesting device.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
Systems and methods for performing sentiment analysis using natural language processing techniques are provided. A method includes: receiving an input dataset comprising a plurality of natural language sentences and a plurality of sentiment labels; pre-processing the input dataset to convert each natural language sentence into a string diagram representation; converting each string diagram into embedded representations; determining, using a hybrid deep learning model, a predicted sentiment label associated with each embedded representation, wherein each predicted sentiment label is associated with a respective probability that each natural language sentence belongs to a first class; identifying for each predicted sentiment label, a noise level; and optimizing a performance of the hybrid deep learning model by updating one or more parameters of the hybrid deep learning model.
Systems, apparatuses, methods, and computer program products are disclosed for dynamic model robustness evaluation. An example method includes receiving a robustness assessment request and retrieving (i) a model, (ii) a dataset, and (iii) a corresponding response set. The example method further includes determining a data correlation set and generating an adaptive noise scale set for each observation of the plurality of observations. The example method further includes generating an adaptive perturbed response set and determining a robustness result. The example method further includes causing performance of a robustness management action
Example modular components within a financial services platform can include a processor executing instructions to generate at least one API facade using a domain-specific language associated with a predefined framework. The API facade is stored in a centralized developer portal, enabling access and seamless integration into the platform. A core application programming interface layer exposes platform functionalities, facilitating interaction between the API facade and external systems. The examples can further include an API façade engine operably coupled to the core API layer, configured to translate the exposed functionalities to conform to at least one of multiple competing API standards. This architecture streamlines the development, deployment, and interoperability of financial services across diverse applications and platforms, enhancing scalability, adaptability, and user experience.
In certain examples, a method is described that may involve transmitting a set of conversations. For each conversation within this set, the method may include tracking a series of display metrics associated with each conversation, storing these metrics, and pairing each conversation with another. The method can further involve generating a win-rate metric for each pair of conversations, using the stored display metrics as a basis. Additionally, the method may include receiving a selection of a particular conversation from the set and subsequently retrieving a group of metrics related to the selected conversation. The group of metrics can include the win-rate metric for both the selected conversation and its paired conversation. The method may include transmitting a display signal that corresponds to the retrieved set of conversation metrics.
Various embodiments are generally directed to techniques for dynamic connectivity between computing entities. Some embodiments are particularly directed to an exchange controller that dynamically establishes and destroys dedicated connections between different computing entities in an on-demand manner that restrict unnecessary network connectivity. In several embodiments, a private network may connect the exchange controller to a first set of one or more computing entities, such as applications in a private cloud. In several such embodiments, the exchange controller may utilize virtual private networks (VPNs) to establish secure communication between the first set of one or more computing entities and a second set of one or more computing entities external to the private network, such as a server or database located in an external cloud.
A computer-implemented method, apparatus, and computer program product for identity based pseudo-random number generation are provided. An example method includes receiving a request for a pseudo-random number selecting a first attribute associated with a first user where the first attribute is associated with a first attribute category that is assigned a first prime number and obtaining a first value for the first attribute. The method further includes selecting a second attribute associated with the first user where the second attribute is associated with a second attribute category that is assigned a second prime number and obtaining a second value for the second attribute. The method includes generating a pseudo-random number based upon the first value and the second value.
Systems, apparatuses, methods, and computer program products are disclosed for generating a dynamic prioritized list of migration tasks for an application. An example method includes identifying, by an application discovery engine and for an application, a set of application components, and generating, by a migration engine, a set of migration tasks based on the set of application components. The example method also includes determining, by a task prioritization analysis engine, a task priority score for each migration task in the set of migration tasks, and determining, by the migration engine, a hierarchical ordering for each migration task of the set of migration tasks. The example method also includes generating, based on the hierarchical ordering and a task priority score for each migration task, the dynamic prioritized list of migration tasks, wherein the dynamic prioritized list of migration tasks comprises an ordered sequence of a subset of migration tasks.
The present disclosure relates to exchanging information between a start node and an end node. Based on the information session keys for a connection comprising the start node, the end node, and at least one intermediate node are established. The session keys include a data encryption session key and a Message Authentication Code (MAC) session key. The data is encrypted using the data encryption session key at the start node. MAC is generated using the MAC session key. The encrypted data is relayed, via the at least one intermediate node, from the start node to the end node without the at least one intermediate node re-encrypting the data.
An example computer system for capturing security information can include: one or more processors; and non-transitory computer-readable storage media encoding instructions which, when executed by the one or more processors, causes the computer system to create: a dashboard engine programmed to generate a dashboard with the security information thereon; a remediation engine programmed to track remediation of one or more security vulnerabilities; and a report generator engine programmed to generate a report including the security information and the one or more security vulnerabilities, wherein dissemination of the report is controlled.
A method includes receiving, by a beneficiary computing system from an intermediate computing system, a digitally signed cross-border message. The digitally signed cross-border message is signed using at least one of a signedData cryptographic message syntax, detached signedData cryptographic message syntax, or signcryptedData cryptographic message syntax. The method includes retrieving, by the beneficiary computing system, a public key of the intermediate computing system or an originating computing system. The method includes verifying at least one of the digitally signed cross-border message or the intermediate computing system comprising determining, by the beneficiary computing system, whether unsigncryption and path validation of the intermediate computing system is successful. The method includes approving, by the beneficiary computing system, a cross-border payment based at least in part on verifying the at least one of the digitally signed cross-border message or the intermediate computing system.
System and techniques for indirectly modeling a phenomenon using a virtual environment are described herein. A set of behavioral conditions specific to an entity in a virtual environment can be obtained. These the conditions pertain to behaviors exclusive to the virtual environment. The behavior of the entity in the virtual environment is tracked in relation to these behavioral conditions to create a behavioral metric. Based on the behavioral metric, a predicted action value that corresponds to an activity not available in the virtual environment is generated for the entity. A representation of the predicted action value can then be transmitted for use in predicting entity behavior with respect to the activity not available in the virtual environment.
A63F 13/69 - Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor by enabling or updating specific game elements, e.g. unlocking hidden features, items, levels or versions
Systems, apparatuses, methods, and computer program products are disclosed for generating a predictive valuation for a non-fungible token (NFT). An example method includes generating, by a NFT valuation engine and using a valuation machine learning framework, a plurality of contribution features of the NFT, where each contribution feature corresponds to an attribute of the NFT and each contribution feature is associated with a feature type. The example method further includes determining a plurality of per-feature prediction contribution scores, wherein each per-feature prediction contribution score corresponds to a contribution feature. The example method further includes determining a predictive valuation score for the NFT based on each per-feature prediction contribution score. The example method further includes providing, by a communications hardware, a predictive valuation report for the NFT based on at least one of the plurality of per-feature prediction contribution scores or the predictive valuation score.
System and techniques for identifying conflicts between rules in a rule engine using semantic matching are described herein. A user-provided rule, conforming to a specified rule standard, is obtained via a user interface. A corresponding vector embedding is generated by translating the rule into a high-dimensional representation reflecting its semantic properties. This embedding is then used to search for a set of similar rules in a rule repository, enabling rapid detection of potential conflicts or redundancies. The resulting similar rules are displayed to the user for review prior to installing the new rule, thus improving the consistency and reliability of rule-based systems.
Systems, apparatuses, methods, and computer program products are disclosed for generating representative training data. An example method includes comparing, by data analysis circuitry, a labeled dataset to a target dataset. The example method also includes generating, by training data circuitry, a training dataset based on the comparison, wherein the training dataset comprises at least a portion of the labeled dataset supplemented by a synthetic dataset. The example method also includes training, by modeling circuitry, a model using the training dataset.
Various examples are directed to computer-implemented systems and methods for predictive analysis of technology infrastructure capacity requirements. A method includes receiving a product roadmap input indicating technological requirements of an enterprise, and analyzing the product roadmap input to locate and extract capacity data from the product roadmap input. Using machine learning, technology infrastructure capacity requirements are predicted for the enterprise based on the capacity data. The technology infrastructure capacity requirements are validated, and technological resources are determined to meet the technology infrastructure capacity requirements. When the technology infrastructure capacity requirements are validated, the technological resources are automatically provisioned to meet the technology infrastructure capacity requirements.
Systems and techniques for secure communications and distribution of random values, produced from at least two satellite entropy sources, are described. These random values may be provided by respective quantum random number generators (QRNGs) at separate satellites, and optionally combined with values from ground-based entropy sources (e.g., QRNGs at terrestrial locations). An example method includes: receiving a first random value and a second random value via at least one satellite communication, where the first random value is generated by a first QRNG at a first satellite, and the second random value is generated by a second QRNG at a second satellite; and generating a cryptographic key based on the first random value and the second random value. The cryptographic key may be produced by a key derivation function that combines the random values, and the cryptographic key may be used to establish a secure communication session.
Systems and methods for attribute based access control on a data lake. The systems and methods include receiving a data file and metadata associated with the data file, storing the data file in a database and storing the metadata in a data catalog. The metadata is assigned a domain access configuration and an attribute access configuration. The systems and methods further include receiving a query for the data file from a user, where the user is assigned a persona, where persona comprises a permission level. Syntax of the query is evaluated in addition to access to the query through steps including evaluating the permission level of the assigned persona against the domain access configuration and evaluating the permission level of the assigned persona against the attribute access configuration. In response to determining that the query fails to satisfy one or more of the evaluations, the query is then rejected.
Systems, apparatuses, methods, and computer program products are disclosed for preparation of a quantum state encoding an approximate normal distribution (QSEAND) in a set of qubits. An example method includes initializing the set of qubits by preparing the set of qubits in an initial quantum state. The example method also includes encoding the approximate normal distribution in the quantum state of the set of qubits, wherein encoding the approximate normal distribution comprises preparing the set of qubits to be in a quantum state representing a plurality of Fourier coefficients, and applying an inverse quantum Fourier transform to the set of qubits in the quantum state representing the plurality of Fourier coefficients to obtain the QSEAND. The example method also includes utilizing the QSEAND, wherein the utilization alters or transfers the QSEAND.
Various embodiments, relate to a system of lockers including a plurality of tracks and a plurality of walls. At least two of the plurality of walls slidably coupled to at least two of the plurality of tracks. Four of the plurality of walls form four sides of a locker cavity. The system also includes a plurality of doors. Each of the plurality of doors are oriented perpendicular to the plurality of the walls. A first door of the plurality of doors is coupleable to a second door of the plurality of doors so as to form a third door, and at least one of the plurality of doors form one side of the locker cavity. The system also includes a back wall, which forms one side of the locker cavity. The system further includes a lock for securing positions of the plurality of walls and of the plurality of doors.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G07C 9/00 - Individual registration on entry or exit
93.
Systems and methods for financial operations performed at a contactless ATM
An automated teller machine (ATM) comprises a network interface circuit enabling the ATM to exchange information over a network, an input/output device configured to exchange data with a mobile wallet circuit on a device associated with a user, and a processing circuit communicably engaged to the network interface circuit and the input/output device and comprising a processor and a memory where the memory is structured to store instructions that are executable by the processor and cause the processing circuit to receive, by the input/output device, a token from the mobile wallet circuit, determine whether the token is associated with a financial institution (FI) associated with the ATM, and transmit, in response to determining that the token is not associated with the FI, the token to a third party computing system without detokenizing the token.
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
G07F 19/00 - Complete banking systemsCoded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
An example computer system for authenticating an electronic communication can include: one or more processors; and non-transitory computer-readable storage media encoding instructions which, when executed by the one or more processors, causes the computer system to create: a notification module programmed to generate a validation code for the electronic communication; and a fraud validation module programmed to accept the validation code and other contextual information associated with the electronic communication to determine an authenticity of the electronic communication.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
95.
AUTOMATIC GENERATION OF BEHAVIORAL TEST CASES FOR NATURAL LANGUAGE PROCESSING USING CLUSTERING AND PROMPTING
Systems and methods for automatic generation of behavioral test cases using clustering and prompting are provided. A method includes accessing an input dataset comprising text data and transforming the text data into a set of embedding vectors using a first large language model (LLM). The method also includes performing dimensional reduction to generate a set of lower-dimensional features and generating a first set of clusters from the set of lower-dimensional features. The method also includes extracting representative data elements from each cluster and generating a set of minimal functionality test (MFT) cases by prompting a second LLM with the representative data elements. The method also includes clustering the MFT cases and testing a downstream machine learning model using the MFT cases.
Systems and methods for exception handling of alternative recordkeeping of data files for entities are described. The systems and methods include receiving a set of files, where each file includes a set of record. Each file is merged to create a merged file including the set of records. An appended merged file is generated by, for each record in the merged file, evaluating the record syntax to determine whether the syntax is valid or invalid and assigning a corresponding syntax flag to the record, and evaluating content of the record to determine whether the content is ready for further processing and assigning a corresponding record ready flag including a record-valid or record-invalid or record partially-valid. The appended merged file is then transmitted, for instance, for further processing.
Systems and methods are disclosed herein for scenario generation and analysis. An example method includes receiving and event and determining a subject matter context to the event. The example method also includes modifying the event based on the subject matter context to prepare a contexed event and generating a prompt based on the contexed event. The example method also includes selecting an agent model based and determining whether the subject matter context relates to a treasury and an associated persona. The example method also includes identifying a historical contexed event from an event corpus that includes pairs of contexed events and descriptions of impacts to a related subject-matter context, and generating a predictive treasury scenario based on the historical contexed event, the treasury, the persona, and the contexed event. The example method also includes generating a risk assessment of the possible response and a response to the contexed event.
Systems, method, and computer readable medium (CRM) for multi-level validation using a unified containerized framework. Some systems include a data processing system including memory and one or more processors configured to receive, from a user device, a protected record authorization for obtaining a plurality of protection records. The processors further configured to obtain, using a protected data channel, the plurality of protection records from each control node of the plurality of control nodes based on performing a handshake. The processors further configured to generate, based on the plurality of protection records, a set of tokens encapsulating a metadata object and store the set of tokens. The processors further configured to generate a root control structure to apply a plurality of operational rules for metadata object updates. The processors further configured to detect, using the root control structure, at least one off-chain event or condition and update the metadata object.
A computing system may determine, for each of a plurality of data records, a corresponding bit validation score that encodes a corresponding data validation answers for a corresponding data record and may store, an integer value of the corresponding bit validation score for each of the plurality of data records. The computing system may select a perspective from a plurality of perspectives each associated with a corresponding one or more data quality rules and may perform one or more bitwise operations between a bit filter score associated with a data quality rule of the perspective and the corresponding bit validation score for each of the plurality of data records to determine whether the plurality of data records meet the data quality rule. The computing system may output an indication of whether the plurality of data records meet the data quality rule.
Systems and methods are disclosed herein for automatic distributed security logging. An example method includes detecting, by security agent circuitry, a security event related to a computer network, and recording, by logging circuitry, an indication of the security event to a storage element belonging to the computer network. The example method also includes determining, by the security agent circuitry, an impact level of the security event, and processing, by ledger circuitry, the security event based on the impact level to produce a ledger security event. The example method also includes selecting, by the ledger circuitry, a number of distributed ledger nodes of a distributed ledger for consensus based on the impact level, and broadcasting, by the ledger circuitry, an indication of the ledger security event to a set of distributed ledger nodes numbering at least the selected number of distributed ledger nodes.
