Abstract: An electronic device for neural network training includes at least one processor and one or more memories configured to provide or train: a generative adversarial network (GAN) using a generator and a discriminator for: receiving a plurality of training cases; and training the generative adversarial network, based on the plurality of training cases, to classify the training cases; wherein the generator generates hard negative examples for the discriminator.

Abstract: Systems and methods are provided for detecting sub-optimal performance of one or more virtual computing platforms. Usage data representing user activity, and performance data representing computing hardware resource utilization, is collected from a plurality of virtual machines hosted on one or more virtual computing platforms. The usage data and performance data is then analyzed along with configuration data representing the hardware components of the computing devices operating the virtual computing platform.

Abstract: An electronic device includes a communication interface and at least one processor configured for: transmitting to or receiving from a second electronic device over proximity-based communication channel an introduction message including a first encryption key; receiving, from a server via the at least one communication interface, a challenge notification providing notification of a challenge to be completed to initiate a data process, the challenge notification including or providing access to at least one data field associated with a verification challenge; identifying, from the at least one data field, an encrypted challenge response value; decrypting the encrypted challenge response value with a key corresponding to the first encryption key; and transmitting the decrypted challenge response value to the server to complete the challenge to initiate the data process.

Abstract: A method for generating visual representations of financial interests includes: receiving an input data set including one or more data structures storing data fields and data values representative of financial interests; extracting, from the input data, one or more extracted features from the funds, the extracted features collectively indicative of a distance between different funds; generating one or more clusters of funds, based on the extracted features of the funds; determining, based on identified differences between one or more funds relative to at least one other fund in a corresponding cluster of funds, one or more fund anomalies based on the one or more extracted features; generating one or more adjustment recommendations based on the one or more fund anomalies, the one or more adjustment recommendations representing control instruction sets for automatically modifying characteristics of the corresponding fund.

Abstract: Embodiments described herein relation to IT incident management that can involve predictive analytics, prescriptive analytics, and descriptive analytics. An IT incident management platform can enable IT incident solution prediction using prescriptive models and natural language processing. An IT incident management platform can enable IT incident ticket volume prediction using predictive models and natural language processing. An IT incident management platform can generate visual elements for display at an interactive interface that represents data centre topology network graphs using descriptive models.

Abstract: A system for processing data within a Trusted Execution Environment (TEE) of a processor is provided. The system may include: a trust manager unit for verifying identity of a partner and issuing a communication key to the partner upon said verification of identity; at least one interface for receiving encrypted data from the partner encrypted using the communication key; a secure database within the TEE for storing the encrypted data with a storage key and for preventing unauthorized access of the encrypted data within the TEE; and a recommendation engine for decrypting and analyzing the encrypted data to generate recommendations based on the decrypted data.

Abstract: A method for dynamic incident management for a computer infrastructure includes: receiving, via a network interface, end-user experience data associated with a plurality of end-user devices; storing the end-user experience data for a corresponding end-user device in an infrastructure database node corresponding to a location of the of the end-user device; upon determining that the end-user experience data for the corresponding end-user device indicates a latency issue at the end-user device, traversing the corresponding infrastructure database node to determine whether a threshold number of latency issues have occurred at the location within a defined time period; when the threshold number of latency issues have occurred, mapping the latency issues to a system performance alert received within a mapping time threshold as a potential root cause; and triggering the execution of response instructions based on the potential root cause.

Abstract: A security device that elicits at least one dynamic response upon acceleration, or upon change of orientation with respect to gravity, wherein the dynamic response continues after cessation of the acceleration or the change of orientation. In addition, the dynamic response can be optical, such that it is visually observable by an unaided human eye. Alternatively, the response can be machine readable. In some cases, the dynamic response has duration of from about 0.01 s to about 100 s, or from about Is to about 10 s.

Abstract: Embodiments generally relate to the field of reward processing, and more particularly, systems, methods, and computer readable media for digital reward processing utilizing distributed ledger technology. Distributed ledger technology is utilized wherein distributed ledgers are stored on a plurality of node computing devices, the distributed ledgers including sequential entries that are cryptographically linked to one another.

Abstract: Computer-implemented systems and methods are provided for improved generation and control of conversations. A computing device is utilized to control or simulate conversation using estimated contextual cues extracted from profile information or prior responses. The computing device is configured to automatically tailor a flow of a conversation to an effort to improve relevancy and engagement without the need of a human operator to manually tailor the conversation, which, for example, could be impractically expensive. A structured workflow is maintained in the form of a series of conversation decisions, and a machine learning engine is utilized to maintain a continuously trained data structure that generates predictions that bias conversation decisions (e.g., by weighting tree options) for tailoring the conversation flow.

Abstract: A system and method for testing system vulnerabilities are provided. The method may include: training, by a processor, a machine learning model and agent to generate a payload to test vulnerabilities in the application by: selecting one or more input data from the action space to form an action data; electronically providing the action data as an input to the application; monitoring utilization of one or more system resources in response to the action data being inputted to the application; determining a score of utilization based on a result of the monitoring; determining a corresponding reward score for the action data based on the score of utilization; and identifying one or more of the action data to form a pool of candidate data for the application.

Abstract: A bid platform for electronic commerce uses smart contracts and a distributed ledger to manage bids and offers for products. The bid platform receives a bid for a product, generates a bid event on a distributed ledger using the smart contracts, propagates the bid event to merchants using the smart contracts and the distributed ledger, receives one or more offers, generates one or more offer events on the distributed ledger using the smart contracts, propagates the one or more offer events using the smart contracts and the distributed ledger, and receives an accepted offer.

Abstract: Systems, methods, and non-transient machine-interpretable data representing executable instruction sets and/or other products for the processing of data for the secure creation, administration, manipulation, processing, and storage of electronic data useful in the processing of payment transactions and other secure data processes. In various aspects and embodiments the disclosure provides secure means for the authorization of sensitive and other data processes subject to controlled access. Such processes include, for example the creation, administration, authorization, virtualization, storage, and other manipulation or processing of electronic data representing characteristics of, instructions for, and information associated with consumer, business, and other payment accounts, and other forms of secure payment elements, such as payment tokens; and data useful in processing transactions using such accounts and elements.

Abstract: Computer implemented methods and systems are provided for generating one or more test cases based on received one or more natural language strings. An example system comprises a natural language classification unit that utilizes a trained neural network in conjunction with a reinforcement learning model, the system receiving as inputs various natural language strings and providing as outputs mapped test actions, mapped by the neural network.

Abstract: A control platform that involves a natural language engine with a risk-based corpora, a rules engine with feature vectors from labelled change records, and topic model to generate an expected label for an additional change record based on training data generated from the labelled change records and the risk-based corpora.

Abstract: There is provided a neural network system for detection of domain generation algorithm generated domain names, the neural network system comprising: an input receiver configured for receiving domain names from one or more input sources; a convolutional neural network unit including one or more convolutional layers, the convolutional unit configured for receiving the input text and processing the input text through the one or more convolutional layers; a recurrent neural network unit including one or more long short term memory layers, the recurrent neural network unit configured to process the output from the convolutional neural network unit to perform pattern recognition; and a classification unit including one or more classification layers, the classification unit configured to receive output data from the recurrent neural network unit to perform a determination of whether the input text or portions of the input text are DGA-generated or benign domain names.

Abstract: Systems and methods for computationally generating a set of more “stable” configuration default values that are used for traceability and improving reproducibility of machine learning approaches. Hash values are generated based on a merged/modified configuration and both configuration content and hash are stored together in one or more data structures. These data structures can be used to link back to the actual values used in experiments.

Abstract: Embodiments described herein provide an application programming interface and framework for a web application firewall single policy model. The framework can layer on top of a firewall platform that provides web application specific widgets that may be toggled and configured to enable or disable certain firewall actions on a per application basis. The framework includes a security stack that defines the order for the widgets. The security stack can provide the ability for a single policy model to be used for the firewall and allows for per application customizations.

Abstract: Security documents often incorporate security devices to prevent or hinder counterfeiters. Disclosed herein are security devices that include a fluid or fluids within the devices. Such devices, and security documents that include them, afford new techniques to check whether a security document is a legitimate or counterfeit copy.

Abstract: Systems, methods and non-transitory computer readable media may be provided for the management of data related to risk exposure. A system may be provided including one or more utilities configured to receive data from a plurality of data sources; a rules engine for applying one or more logical rules that are triggered by one or more conditions associated with the integrity of the received data; and one or more utilities configured to apply the one or more logical rules to validate received data and automatically request updated data from a subset of the plurality of data sources where the integrity of the received data does not meet a predefined threshold. Other systems may be provided including units configured for the determination of risk exposure, and the identification of a tiered risk exposure analysis. Corresponding methods and non-transitory computer readable media may be provided.