Abstract: The invention relates to alternate user communication routing for a one-time credential. When a user is determined to be an unauthorized user, the unauthorized user may be provided with an alternative one-time credential (e.g., one-time password, or the like) in response to the user trying to take an action (e.g., to access the organization systems in order to access information). When the unauthorized user tries to utilize the alternative one-time credential, the organization may identify the user as unauthorized and determine how to respond to the unauthorized user. In addition to the alternative one-time credential, one or more additional alternate treatments may be presented to the unauthorized user in order to identify, track, and/or prevent access by the unauthorized user.

Abstract: A system for event-based peer-to-peer resource transfers. The system comprising: a controller configured for tracking and confirming resource transfers, the controller being further configured to: generate a resource transfer for transferring a resource from a first user device to a second user device, wherein the resource transfer comprises a conditional event for triggering a transfer of the resource, and wherein the conditional event is accepted by the first user device and the second user device; receive the resource from the first user device, wherein the resource is held separate from the first user device and the second user device; determine that the conditional event has been executed by at least one of the first user device and the second user device; and based on the determining that the conditional event has been executed, trigger the transfer of the resource to the second user device.

Abstract: A system and methods for alternate user communication routing are described. Unauthorized users are identified and alternate treatments are provided in order to deter unauthorized access and create opportunities for data collection. The use of a varied set of alternate treatments provides an enhanced view of unauthorized user behavior and an increased ability to track future unauthorized user actions by recording various user identity/communication characteristics specific to known unauthorized users. Alternate treatments may be provided randomly based on a set of alternate treatments previously provided to a specific user, or may be varied based on an identified group of unauthorized users presumed to be acting in concert.

Abstract: Embodiments of the present invention provide a system and methods to mitigate poisoning attacks within machine learning systems. The invention includes an improved data analysis approach to train an ensemble of machine learning models to analyze received data and label the data in a non-binary fashion to indicate likelihood that certain data has been injected abnormally and should not be used for training purposes. The resulting dataset from the ensemble is assessed to determine convergence of model labeling and to detect outlier data labeling among models in the ensemble. Confidence scores for clustered interaction data may be performed on varied sets of training data populations and using a number of models. Output from the various training/model mixes are fed to a machine learning model to compare ensemble accuracy between different model sets and select the most accurate ensemble combination.

Abstract: Embodiments of the present invention provide a system and methods to prevent poisoning attacks in machine learning systems in real time. The invention includes methods for blocking the injection of abnormal data into training data sets used to train machine learning models for the identification of malfeasant activity by blocking certain data from entering the machine learning training dataset in real time, blocking certain interactions from being completed in real time, or placing holds on certain resources or users according to patterns detected by the ensemble of machine learning models. Various thresholds may be set manually or identified through the machine learning algorithm in order to determine which interactions or users should be blocked.

Abstract: Systems, computer program products, and methods are described herein for machine learning based system for authorization of autonomous resource transfers between distributed IoT components. The present invention is configured to receive, from a first autonomous IoT device, a transaction authorization request to execute a transaction with a second autonomous IoT device; receive information associated with the first autonomous IoT device, information associated with the second autonomous IoT device, and information associated with the transaction; initiate an execution of one or more machine learning algorithms; determine that the first autonomous IoT device is authorized to execute the transaction with the second autonomous IoT device; transmit a transaction authorization to the first autonomous IoT device to execute the transaction; and receive, from the first autonomous IoT device, an indication that the transaction has been executed.

Abstract: A system and methods for alternate user communication routing are described. Unauthorized users are identified and alternate treatments are provided in order to deter unauthorized access and create opportunities for data collection. The use of a varied set of alternate treatments provides an enhanced view of unauthorized user behavior and an increased ability to track future unauthorized user actions by recording various user identity/communication characteristics specific to known unauthorized users. Alternate treatments may be provided randomly based on a set of alternate treatments previously provided to a specific user, or may be varied based on an identified group of unauthorized users presumed to be acting in concert.

Abstract: The invention relates to alternate user communication routing for a one-time credential. When a user is determined to be an unauthorized user, the unauthorized user may be provided with an alternative one-time credential (e.g., one-time password, or the like) in response to the user trying to take an action (e.g., to access the organization systems in order to access information). When the unauthorized user tries to utilize the alternative one-time credential, the organization may identify the user as unauthorized and determine how to respond to the unauthorized user. In addition to the alternative one-time credential, one or more additional alternate treatments may be presented to the unauthorized user in order to identify, track, and/or prevent access by the unauthorized user.

Abstract: Embodiments of the present invention provide a system for security analysis and authentication. The system can generate a one time password (OTP) signature for a user using a neural network machine learning system. This OTP signature can be analyzed by multiple applications that each utilize different certain authentication verification matching requirements, such that security concerns and strengths of varied downstream applications are taken into account on an individual application basis. Each application determines an authentication value for the user based on the OTP signature, and access or other permissions are granted in response to the authentication value meeting or exceeding a threshold value for that application.

Abstract: A system for machine learning-based real-time electronic data quality checks in online machine learning and AI systems is provided. In particular, the system may comprise a machine learning module which receives input data from a data quality learning module which serves to perform filtering or alteration functions on incoming data during the training and/or live phases of the machine learning module. Over time, the data quality module may increasingly become efficient and accurate at assessing incoming data to determine the data quality. In turn, improving data quality of input data may ensure that the various neural networks within the system produce adaptively accurate output values to drive the decisioning processes of the system.

Abstract: The invention relates to alternate user communication routing for a one-time credential. When a user is determined to be an unauthorized user, the unauthorized user may be provided with an alternative one-time credential (e.g., one-time password, or the like) in response to the user trying to take an action (e.g., to access the organization systems in order to access information). When the unauthorized user tries to utilize the alternative one-time credential, the organization may identify the user as unauthorized and determine how to respond to the unauthorized user. In addition to the alternative one-time credential, one or more additional alternate treatments may be presented to the unauthorized user in order to identify, track, and/or prevent access by the unauthorized user.

Abstract: The invention relates to alternate user communication routing for a one-time credential. When a user is determined to be an unauthorized user, the unauthorized user may be provided with an alternative one-time credential (e.g., one-time password, or the like) in response to the user trying to take an action (e.g., to access the organization systems in order to access information). When the unauthorized user tries to utilize the alternative one-time credential, the organization may identify the user as unauthorized and determine how to respond to the unauthorized user. In addition to the alternative one-time credential, one or more additional alternate treatments may be presented to the unauthorized user in order to identify, track, and/or prevent access by the unauthorized user.

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: A system for integrated natural language programming (“NLP”) and event analysis provides threat detection in computing systems. In particular, the system may use an NLP unit to analyze threat logs from various sources according to multiple different metrics and/or analysis paradigms. Upon completing the analysis, the system may extract, via machine learning, event and/or threat patterns which may be integrated into the system's threat detection processes.

Abstract: The invention relates to alternate user communication routing for a one-time credential. When a user is determined to be an unauthorized user, the unauthorized user may be provided with an alternative one-time credential (e.g., one-time password, or the like) in response to the user trying to take an action (e.g., to access the organization systems in order to access information). When the unauthorized user tries to utilize the alternative one-time credential, the organization may identify the user as unauthorized and determine how to respond to the unauthorized user. In addition to the alternative one-time credential, one or more additional alternate treatments may be presented to the unauthorized user in order to identify, track, and/or prevent access by the unauthorized user.

Abstract: Embodiments of the present invention provide a system for active malfeasance examination and detection based on dynamic graph network flow analysis. The system is typically configured for extracting resource distribution information for a plurality of resource pools, generating a dynamic graph comprising a plurality of nodes and a plurality of edges, calculating custom reputation values for each of the plurality of nodes, identifying a first node of the plurality of nodes comprising a custom reputation value associated with a malfeasance, identifying a user associated with the first node and identify user information associated with the user, communicating a resource distribution request to the user based on the identified user information, receiving an acceptance of the resource distribution request from a computing device of the user, and executing one or more remediation actions on one or more resource pools of the user.

Abstract: Embodiments of the present invention provide a system for generative adversarial network training and feature extraction for biometric authentication. The system collects electronic biometric data of a user from one or more data sources, and stores the collected electronic biometric data as a biometric user account for the user in a personal NoSQL database library associated with the user. A generative adversarial neural network system then determines improved biometric feature selection and improved model refinements for existing biometric authentication models based on the biometric account for the user in the personal library associated with the user. The system can then determine user exposure levels for different authentication channels, including certain biometric authentication channels. A custom adversarial strategy for general adversarial network attacks is then established based on the user exposure levels to generate a biometric authentication process that is more accurate and secure.

Abstract: A system for reconfiguring neural network architecture responsive to a system state is provided. A controller for modifying a neural network learning engine is configured to monitor a data stream having a data pattern by comparing the data pattern to a trained data pattern; identify a change in the data pattern of the data stream; determine a state of the neural network learning engine, the state defining one or more neural network parameters for monitoring the data stream with the neural network learning engine; and in response to identifying the change in the data pattern and determining the state, reconfigure an architectural configuration of the neural network learning engine by modifying the one or more neural network parameters.

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: 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.