Abstract: A stent apparatus, system, and method that senses wall shear stress by measuring fluid flow at localized areas within the stent, that processes measured information through an integrated circuit, and selectively sends power to mechanically controllable stent surfaces which results in localized geometric changes. In various embodiments the stent apparatus, system, and method sends data to outside the body in real time.

Abstract: In some embodiments, a method can include identifying detection coverage of a set of adversarial techniques based on telemetry data and a detection instance of an environment. The method can further include determining a subset of detection coverage that has a metric value below a metric value threshold and among the detection coverage for the set of adversarial techniques. The method may further include identifying at least one detection instance associated with the subset of detection coverage. The method can further include presenting, via a graphical user interface, a representation of at least one of the subset of detection coverage or the at least one detection instance associated with the subset of detection coverage. The method can further include updating the subset of detection coverage based on the telemetry data, the detection instance, or the at least one detection instance to improve the metric value.

Abstract: Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N.

Abstract: A Merkle tree-based data management method may comprise: aligning data into two-dimensional square matrix; calculating a hash value of each node of the two-dimensional square matrix; calculating hash values of each row of the two-dimensional square matrix; generating an additional column with nodes having the hash values of each row; calculating hash values of each column of the two-dimensional square matrix; generating an additional row with nodes having hash values of each column; and calculating a Merkle root by concatenating the hash values of the additional column and the hash values of the additional row.

Abstract: Embodiments include a computing device that executes software routines and/or one or more machine-learning architectures providing improved omni-channel authentication solutions. Embodiments include one or more computing devices that provide an authentication interface by which various communication channels may deposit contact or session data received via a first-channel session into a non-transitory storage medium of an authentication database for another channel to obtain and employ (e.g., verify users). This allows the customer to access an online data channel and enter the contact center through a telephony communication channel, but further allows the enterprise contact center systems to passively maintain access to various types of information about the user's identity captured from each contact channel, allowing the call center to request or capture authenticating information (e.g.

Abstract: The methods and systems are operable to protect a computing environment from attack. The methods and systems incorporate a preventative ability with similar attributes to an Antivirus/Anti-malware technique suitable for use on home user or similar protected computing environments with no or minimal centralized human administrative resources using natural language.

Abstract: Embodiments described herein provide for a computer that detects one or more keywords of interest using acoustic features, to detect or query commonalities across multiple fraud calls. Embodiments described herein may implement unsupervised keyword spotting (UKWS) or unsupervised word discovery (UWD) in order to identify commonalities across a set of calls, where both UKWS and UWD employ Gaussian Mixture Models (GMM) and one or more dynamic time-warping algorithms. A user may indicate a training exemplar or occurrence of call-specific information, referred to herein as “a named entity,” such as a person's name, an account number, account balance, or order number. The computer may perform a redaction process that computationally nullifies the import of the named entity in the modeling processes described herein.

Abstract: An access control server may store a private cryptographic key. The private cryptographic key corresponds to a public cryptographic key. The public cryptographic key is stored on a blockchain as part of an autonomous program protocol. The access control server may receive access control setting related to the autonomous program protocol. The access control server may receive a request for accessing the autonomous program protocol stored on the blockchain. The access control server may review the request. The access control server may determine the request is in compliance with the policies specified in the setting. The access control server may create, using the private cryptographic key, a digital signature for the request and generate a response including the digital signature. A successful verification of the digital signature using the public cryptographic key stored in the autonomous program protocol is required by the autonomous program protocol to process the request.

Abstract: A network-accessible service provides an enterprise with a view of all identity and data activity in the enterprise's cloud accounts. The service enables distinct cloud provider management models to be normalized with centralized analytics and views across large numbers of cloud accounts. The service enables an enterprise to model all activity and relationships across cloud vendors, accounts and third party stores. Display views of this information preferably can pivot on cloud provider, country, cloud accounts, application or data store. Using a domain-specific query language, the system enables rapid interrogation of a complete and centralized data model of all data and identity relationships. User reports may be generated showing all privileges and data to which a particular identity has access. Similarly, data reports shown all entities having access to an asset can be generated.

Abstract: A validation device in a communication network is configured to communicate control information bidirectionally via a control plane of the network and access message data via a production plane of the network. The validation device receives key data via the control plane, and accesses a message received via the production plane by a message receiving device. The message includes a signature derived from the first key data. The validation device uses the first key data to check validity of the signature.

Abstract: Geolocating one or more emitters includes obtaining a set of lines of bearing (LOBs) indicative of location(s) of emitter(s), determining intersections of LOBs of the set and generating clusters informed by those intersections, assigning the LOBs of the set to cluster(s) based on proximity, identifying a cluster having the greatest number of assigned LOBs from the set; determining an emitter location area based on a best point estimate for the cluster, and indicating a location of an emitter as the emitter location area. Additional emitters can be located by removing from the set of LOBs those LOBs assigned to the identified cluster, and repeating aforementioned aspects. Initially, the set of LOBs can be selected from a larger collection as a representative subset thereof.

Abstract: Embodiments described herein provide for a fraud detection engine for detecting various types of fraud at a call center and a fraud importance engine for tailoring the fraud detection operations to relative importance of fraud events. Fraud importance engine determines which fraud events are comparative more important than others. The fraud detection engine comprises machine-learning models that consume contact data and fraud importance information for various anti-fraud processes. The fraud importance engine calculates importance scores for fraud events based on user-customized attributes, such as fraud-type or fraud activity. The fraud importance scores are used in various processes, such as model training, model selection, and selecting weights or hyper-parameters for the ML models, among others. The fraud detection engine uses the importance scores to prioritize fraud alerts for review.

Abstract: A system for detecting suboptimal performance of security check operations. The system may include a sensor operable to output sensor data indicative of physical characteristics of a security check environment, an output device, and a processing device comprising a processor and a memory. The security check environment may include at least one of a prohibited object detector, a human patron, an object carried by the human patron, and a human security officer. The processing device may be operable to: determine, based on the sensor data, that security check operations at the security check environment are being performed in a suboptimal manner; and in response to determining that the security check operations are being performed in a suboptimal manner, output alarm data to the output device to cause the output device to output an alarm signal indicative of the suboptimal manner in which the security check operations are being performed.

Abstract: Embodiments described herein provide for passive caller verification and/or passive fraud risk assessments for calls to customer call centers. Systems and methods may be used in real time as a call is coming into a call center. An analytics server of an analytics service looks at the purported Caller ID of the call, as well as the unaltered carrier metadata, which the analytics server then uses to generate or retrieve one or more probability scores using one or more lookup tables and/or a machine-learning model. A probability score indicates the likelihood that information derived using the Caller ID information has occurred or should occur given the carrier metadata received with the inbound call. The one or more probability scores be used to generate a risk score for the current call that indicates the probability of the call being valid (e.g., originated from a verified caller or calling device, non-fraudulent).

Abstract: A method, medium and system for generating a high-rate video for displaying to a user on a display device. The method, medium and system may generate and display the high-rate video by: capturing images for a video at a first frame rate, capturing movement of a display device via a motion sensor, estimating a motion of the camera based on images of the video captured at the first frame rate and the movement of the display device captured via the motion sensor, generating the high-rate video at a second frame rate by up-sampling the video captured at the first frame rate, and displaying the high-rate video to the user.

Abstract: A method includes: generating a manifest of assets during the target time interval; labeling each asset in the manifest of assets with a set of attributes exhibited by the asset during the target time interval; defining a first attribute category exhibiting a first combination of attributes; assigning a first action to the first attribute category; identifying a subset of assets in the manifest of assets matching the first attribute category, each asset in the subset of assets exhibiting a set of attributes including the first combination of attributes; and executing the first action on the first subset of assets.

Abstract: Security systems for microelectronic devices physically lock the hardware itself and serve as a first line of defense by preventing overwriting, modification, manipulation or erasure of data stored in a device's memory. Implementations of the security systems can respond to lock/unlock commands that do not require signal or software interactivity with the functionality of the protected device, and which therefore may be consistent across devices.

Abstract: Disclosed are systems and methods including computing-processes, which may include layers of machine-learning architectures, for assessing risk for calls directed to call center systems using carrier signaling metadata. A computer evaluates carrier signaling metadata to perform various new risk-scoring techniques to determine riskiness of calls and authenticate calls. When determining a risk score for an incoming call is received at a call center system, the computer may obtain certain metadata values from inbound metadata, prior call metadata, or from third-party telecommunications services and executes processes for determining the risk score for the call. The risk score operations include several scoring components, including appliance print scoring, carrier detection scoring, ANI location detection scoring, location similarity scoring, and JIP-ANI location similarity scoring, among others.

Abstract: A method, medium and system for auto-aligning displays of a head/helmet mounted display. The method, medium and system may provide for an auto-alignment of components of a headband, headgear, or a helmet. The method, medium and system may provide for a first sensor mounted to the helmet of a user and configured to communicate and transfer align with a vehicle comprising an inertial navigation system (INS). The method, medium and system may provide for display comprising a second sensor configured to communicate with the first sensor and transfer align the second sensor with the first sensor based on the transfer alignment of the first sensor with the vehicle. The method, medium and system may provide for wherein the first sensor and the second sensor comprise an inertial measurement unit (IMU). Further, the method, medium and system may also provide for the aligning of two displays on the head/helmet relative to each other in real time.

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.