Abstract: Systems and methods are provided for the classification of identified security vulnerabilities in software applications, and their automated triage based on machine learning. The disclosed system may generate a report listing detected potential vulnerability issues, and extract features from the report for each potential vulnerability issue. The system may receive policy data and business rules, and compare the extracted features relative to such data and rules. The system may determine a token based on the source code of a potential vulnerability issue, and a vector based on the extracted features of a potential vulnerability issue and based on the token. The system may select a machine learning modelling method and/or an automated triaging method based on the vector, and determine a vulnerability accuracy score based on the vector using the selected method.

Abstract: Systems and methods are provided for the classification of identified security vulnerabilities in software applications, and their automated triage based on machine learning. The disclosed system may generate a report listing detected potential vulnerability issues, and extract features from the report for each potential vulnerability issue. The system may receive policy data and business rules, and compare the extracted features relative to such data and rules. The system may determine a token based on the source code of a potential vulnerability issue, and a vector based on the extracted features of a potential vulnerability issue and based on the token. The system may select a machine learning modelling method and/or an automated triaging method based on the vector, and determine a vulnerability accuracy score based on the vector using the selected method.

Abstract: An accident detection system for providing movement data for processing using a ML model executed on a mobile device, the movement data being generated by the mobile device, receiving, from the ML model, a first prediction representative of an occurrence of a first accident, in response to receiving the first prediction, providing a first local alert on the mobile device, and selecting one of a first network and a second network for broadcasting a first remote alert to one or more end-points, if the first network is selected, the first remote alert is broadcast over the first network by the mobile device, and, if the second network is selected, the first remote alert is broadcast over the second network by an alerting module that is in communication with the mobile device.