A measure of influence of a sender entity is determined for a message receiving entity based at least in part on an analysis of previous electronic messages sent by the sender entity. An electronic message associated with the sender entity is received. The measure of influence of the sender entity is utilized to determine a security risk associated with the received electronic message.

A computer system, non-transitory computer storage medium, and a computer-implemented method of assessing technical risk using visual pattern recognition in an Information Technology (IT) Service Management System. A data visualization engine and a time series generation engine receive the operational data, respectively. A first representation of the data is generated by the data visualization engine, and a second representation of the data is generated by the time series generation engine. Anomaly patterns are identified by a pattern recognition engine configured to perform feature extraction and data transformation. An ensembler is configured to accept the outputs from two AI anomaly engines and make a final decision of whether anomaly patterns are captured. Risk scores based on the identified anomaly patterns are output by a pattern recognition engine to an automated management system. The anomalies includes information regarding vulnerabilities of devices or components of the IT Service Management System.

Disclosed herein are system, method, and device embodiments for time-based trust token (TBTT) depreciation. In an example embodiment, a service provider system (e.g., a service provider and API service) may receive a connection request including a demographic attribute associated with a first client account from a partner device, match the demographic attribute to client information associated with the first client account, send the partner device a connection request identifier and a URL including a depreciating token, and authenticate a second client account via a login page associated with the URL. Further, the service provider system may receive a verification request including the connection request identifier and the depreciating token, determine a security context of the depreciating token based on a depreciation function and the verification request, and determine, based on the security context, whether to create a connection between the second client account and partner device within the service provider system.

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. The fraud importance engine receives detection feedback, which contacts involved false negatives, where fraud events were undetected but should have been detected.

A method for validating a time function in a network of a vehicle includes: ascertaining a receiving time of a sync message of a master; receiving a follow-up message of the master; ascertaining a receiving time of a further sync message of the master; receiving a further follow-up message of the master; determining a time function of the first client based on the receiving time of the sync message, the receiving time of the further sync message, the transmission time of the follow-up message, and the transmission time of the further follow-up message; ascertaining a synchronized transmission time of a path delay request message from the first client to the master; ascertaining a synchronized receiving time of a path delay response message from the master; receiving a path delay response follow-up message from the master by the first client; and validating a time function of the master.

Disclosed herein are system, method, and device embodiments for time-based trust token (TBTT) depreciation. In an example embodiment, a service provider system (e.g., a service provider and API service) may receive a connection request including a demographic attribute associated with a first client account from a partner device, match the demographic attribute to client information associated with the first client account, send the partner device a connection request identifier and a URL including a depreciating token, and authenticate a second client account via a login page associated with the URL. Further, the service provider system may receive a verification request including the connection request identifier and the depreciating token, determine a security context of the depreciating token based on a depreciation function and the verification request, and determine, based on the security context, whether to create a connection between the second client account and partner device within the service provider system.

A method for verifying a proximity of a user device to a beacon, including broadcasting a frame comprising an encrypted payload, receiving the frame, extracting information from the frame, and verifying the proximity of the user device to the beacon based on the extracted information.

Predictive entity resolution uses a set of identity models to resolve an attribute to one or more associated entities, possibly with respective probabilities, at a particular time. The predictive entity resolution generates the sets of identity models from evidence events received from evidence sources. Each evidence event has at least one attribute and an associated time stamp.

Techniques are described for expediting communications between a first person of an organization associated with a communication platform and a second person not associated with the organization. The first person requests for the communication platform to generate an invitation to communicate with the second person. The first person provides the invitation to the second person directly or via the communication platform. Responsive to receiving an indication that the second person accepts the invitation, the communication platform identifies whether the second person is associated with the communication platform. If the second user is associated with the communication platform, the communication platform modifies an existing user interface associated therewith to enable communications between the first person and the second person. If the second person is not associated with the communication platform, the communication platform generates a limited functionality user interface to enable the communications between the first person and the second person.

A method synchronizes frame counters for protecting data transmissions between a first end-device and a second end-device. The data, in particular data frames, are transferred between the first end-device and the second end-device. The data frames are provided with frame counters to protect the data transfer between the first end-device and the second end-device. The second end-device sends a first data frame to the first end-device. The first data frame contains a marker in its payload data. The first end-device sends back a second data frame as an answer to the second end-device. The second data frame contains a frame counter in the header data, and the second data frame contains the frame counter and the marker in its payload data.