Abstract: An electronic communication security system is typically configured for tracking and monitoring user activity of a user, identifying a trigger based on monitoring and tracking the user activity, communicating with back-end system to extract information associated with a resource entity that is associated with the trigger, communicating with the back-end systems to identify user agreement associated with the user and the resource entity, identifying one or more supplemental resources provided by the resource entity, based on the user agreement, prompting the user to authorize transfer of anonymized user data to the resource entity to receive the one or more supplemental resources, anonymizing the user data and transmit the anonymized user data to the resource entity, in response to transmitting the anonymized user data to the resource entity, receiving the one or more supplemental resources from the resource entity, and transmitting the one or more supplemental resources to the user device.

Abstract: A system for generating a hybrid token architecture for chaining authenticated interactions is provided.

Abstract: Embodiments of the invention are directed to a decentralized block chain regulation architecture. The invention utilizes the collective nature of block chain communication to perform key regulatory and control functions. Instead of relying on a centralized regulatory source, the present system allows the block chain structures themselves to simultaneously function as both regulated and regulatory chains for one another to form an interconnected network of decentralized, regulatory chains. Further, the system allows for control of non-compliant block chains, wherein regulatory chains may issue commands to the non-compliant chains, rewrite data, overwrite an incorrect consensus, or deactivate a chain and remove it from a block chain environment before propagation of an error.

Abstract: Embodiments of the present invention provide a system for security analysis and authentication. The system can analyze, using a deep neural network machine learning system, historical one time password (“OTP”) information, historical information, historical malfeasance information, and historical information for a plurality of users to determine available OTPs. When an authentication request is received, one of the available OTPs is randomly or variedly selected and the user is prompted to provide information along with a response for the OTP. The received information is analyzed against the historical information and an OTP signature is generated for the user. This OTP signature is used to determine whether the user is authenticated for one or more authentication elements.

Abstract: A system is configured for extracting historical information for a first plurality of resource pools, generating a historical dynamic graph based on the historical information, identifying from the historical information, a historical set of resource distribution events associated with a malfeasance, determining from the historical dynamic graph, at least one historical malfeasance pattern, receiving current resource distribution request information for a second plurality of resource pools, generating a current dynamic graph comprising a current plurality of nodes and a current plurality of edges, monitoring the current dynamic graph and identify a current malfeasance pattern, and executing one or more remediation actions on one or more of the second plurality of resource pools associated with the current dynamic graph.

Abstract: A system for modifying electronic records for tracking use is provided. The system comprises a controller configured for transforming an electronic record, the controller comprising a memory device with computer-readable program code stored thereon, a communication device connected to a network, and a processing device, wherein the processing device is configured to execute the computer-readable program code to: receive a request from a user device to access an electronic record during an interaction session; extract a session identifier signature for the interaction session; generate, with a transformation function, one or more modifications for the electronic record based on the session identifier signature; transform the electronic record to a modified record by applying the one or more modifications to the electronic record; and provide the modified record to the user device.

Abstract: An electronic authorization system is typically configured for: receiving electronic activity requests from a plurality of source nodes; analyzing each of the electronic activity requests using a decisioning algorithm, wherein a decision boundary of the decisioning algorithm is dynamically altered while analyzing the electronic activity requests; for each of the electronic activity requests, determining an activity exposure level of the decision boundary based on (i) a distance to the decision boundary and (ii) an amount of information exposed regarding the decision boundary; for each of the plurality of source nodes, determining a source exposure level of the decision boundary based on the activity exposure levels of the decision boundary of the electronic activity requests; and in response to determining that a likelihood of decision boundary profiling by one or more first source nodes exceeds a defined threshold, performing an exposure remediation action.

Abstract: A system for feature relevance visualization optimization is provided. The system comprises a controller configured for modifying placement of features in a relevance visualization. The controller is further configured to: receive interaction data comprising one or more features positioned in the relevance visualization, wherein the one or more features are defined and measurable properties of the interaction data; construct a logical grouping of the one or more features based on a type of each of the one or more features, wherein similar features are collocated in the relevance visualization; construct a machine learning-based grouping of the one or more features based on relevance calculations for the one or more features; combine the logical grouping and the machine learning-based grouping to generate a combined feature placement, wherein the one or more features are repositioned in the relevance visualization; and output the relevance visualization having the combined feature placement.

Abstract: A system for contract-based peer-to-peer resource transfers is provided. The system comprises a controller configured to: generate a resource transfer contract for transferring a resource from a first user device to a second user device, wherein the resource transfer contract comprises a distributed protocol defining a sequential flow of one or more trigger events for triggering a transfer of the resource; distribute the resource transfer contract to the first user device and the second user device; determine that the one or more triggering events have been completed by one or more of the first user and the second user based on communication with the first user device and the second user device; and in response to determining that the one or more triggering events have been completed, transfer the resource to the second user device.

Abstract: A system for analyzing machine learning-derived misappropriation types with an array of shadow models is provided. The system comprises: a controller configured for analyzing an output of a machine learning model, the controller being further configured to: input interaction data into a machine learning model, wherein the interaction data is analyzed using the machine learning model to determine a misappropriation type output associated with the interaction data; identify data features in the interaction data associated with the misappropriation type output; construct an array of shadow models based on the data features, wherein each individual model in the array of shadow models is configured to extract logical constructs from a portion of the data features; and consolidate the logical constructs output by the array of shadow models, wherein consolidating the logical constructs determines a final explanation output for the misappropriation type output determined by the machine learning model.

Abstract: A system is typically configured for customizing interconnectivity of one or more layers associated with a neural network architecture, wherein the neural network architecture is associated with an application, customizing functional transformation of the one or more layers associated with the neural network architecture, wherein each of the one or more layers comprises a custom transformation function, and generating a custom neural network architecture based on customizing the interconnectivity and the functional transformation of the one or more layers.

Abstract: A system for machine learning-derived contract generation is provided. The system comprises: a machine learning engine and a controller configured to: input historical and streaming interaction data into the machine learning engine, wherein the machine learning engine is trained by the historical and streaming interaction data; determine one or more machine learning-derived interaction patterns for a resource transfer between the first user device and the second user device, wherein the one or more machine learning-derived interaction patterns comprise calculated exposure levels for one or more events for completing the resource transfer; based on the machine learning-derived interaction patterns, generate the resource transfer contract for transferring a resource from the first user device to the second user device, wherein the resource transfer contract comprises a sequential flow of the one or more events; and distribute the resource transfer contract to the first user device and the second user device.

Abstract: A system for machine learning data pattern recognition for misappropriation identification is provided. The system comprises a controller configured for learning and identifying misappropriation data patterns.

Abstract: Embodiments of the present invention provide an improvement to conventional biometric authentication systems and techniques by providing an innovative system, method and computer program product for thermal enrichment of biometric authentication data to generate a high-confidence verification of user identity. A collaborative system for receiving data and continuously analyzing the data to determine emerging patterns is provided. The invention provides for the enrichment of biometric authentication data with thermal imaging data in order to discern between authentic data samples in contrast to inanimate copies or models. Furthermore, the invention is designed to detect and analyze liveliness of data samples as a means of authentication.

Abstract: A system for attention-based layered neural network classification is provided. The system comprises: a sequence of layered neural networks; and a controller configured for controlling data routed through the sequence of layered neural networks, the controller configured to: receive interaction data comprising data features, wherein the data features are distinct characteristics of the interaction data; input data features into the sequence of layered neural networks, wherein each sequential layer of the sequence of layered neural networks comprises a heightened rigor level for at least one of the data features; calculate a relevance score output for at least one of the data features at each layer of the sequence of layered neural networks; and integrate the relevance score output from each layer of the sequence of layered neural networks to generate a total relevance score output.

Abstract: Systems and methods for data sharing and transaction processing for high security documents are disclosed. According to one embodiment, a method may include (1) at least one computer processor verifying that a sender of a document is authorized to send the document; (2) the at least one computer processor verifying that a receiver of the document is authorized to receive the document; (3) the at least one computer processor identifying at least one restriction to associate with the document; and (4) the at least one computer processor associating the at least one restriction with the document.

Abstract: Systems and methods for high fidelity multi-modal out-of-band biometric authentication are disclosed. According to one embodiment, a method for multi-mode biometric authentication may include (1) receiving, at a computer application executed by an electronic device, a first input from a first input device on the electronic device; (2) receiving, at the computer application, a second data from a second input device on the electronic device; (3) receiving, at the computer application, a third input from a third input device on the electronic device; and (4) communicating, by the computer application and to a server, the first input, the second input, and the third input. The first input, second input and third input may be received within a predetermined time period, such as five seconds.

Abstract: Systems, computer program products, and methods are described herein for authenticating a user using an application specific integrated circuit embedded within a user device. The present invention is configured to receive an indication that a user has initiated an application on the user device; determine that the application is associated with the application specific integrated circuit embedded within the user device; activate the application specific integrated circuit based on at least determining that the application is associated with the application specific integrated circuit; receive an indication that the user has initiated an execution of an action, via the application, with an entity; and execute the action using the application specific integrated circuit based on at least receiving the indication that the user has initiated the execution of the action.

Abstract: An electronic communication security system is typically configured for continuously tracking and monitoring user activity associated with a user, identifying a trigger based on continuously tracking and monitoring the user activity, wherein identifying the trigger is based on identifying that the user activity meets one or more conditions, determining initiation of an interaction between the user and a resource entity based on identifying the trigger, communicating with back-end systems to extract information associated with the resource entity associated with the interaction, wherein the information comprises an output that is generated by one or more machine learning models, generating exposure characteristics for the interaction based on the output associated with the resource entity and user data associated with the user, wherein the exposure characteristics are unique to the interaction and the user, and in response to generating the exposure characteristics, transmitting the exposure characteristics to

Abstract: A system and method for dynamically optimizing channel interactions and account security are provided. A controller configured for analyzing user interactions is configured to determine an interaction pattern of a user during an interaction with the user over a communication channel; calculate a weighted confidence function for subsequent interactions with the user based on the determined interaction pattern, wherein the weighted confidence function defines authentication and response procedures for the subsequent interactions with the user; and merge the weighted confidence function into a custom user profile for the user across a plurality of communication channels, wherein the user profile maps account vulnerabilities based on the weighted confidence function.