Abstract: A method, system and computer program product for facilitating risk mitigation of information security threats. Data obtained from at least one tracked data source is analyzed for identifying at least one event related to a threat, to be stored in a database comprising date and time of each event identified, enabling generation of threat timeline comprising temporally ordered sequence of each event related to respective threat identified. Features selected using correlation between features from threat timelines in the database and labeling assigned using records of threat usage incidents are extracted from events in threat timeline for the threat which the at least one event related thereto being identified and based thereon a dynamic score indicating an estimated level of risk posed by the threat is calculated using at least one machine learning model for predicting threat usage during a time window defined, enabling risk mitigation based on outputted indication thereof.

Abstract: A dark web monitoring, analysis and alert system comprising a data receiving module configured to receive data collected from the dark web and structured; a Structured Data Database (SDD) connected with the data receiving module, the SDD configured to store the structured data; a Text Search and Analytic Engine (TSAE) connected with the SDD, the TSAE configured to enable advanced search and basic analysis in the structured data; a Knowledge Deduction Service (KDS) connected with the TSAE, the KDS configured to deeply analyze the collected data; the deep analysis comprises extracting insights regarding dark web surfers behavioral patterns and interactions; a Structured Knowledge Database (SKD) connected with the KDS, the SKD configured to store the deep analysis results; and an Alert Service connected with the TSAE and the SKD, the Alert Service configured to provide prioritized alerts based on the deep analysis.

Abstract: A dark web monitoring, analysis and alert system comprising a data receiving module configured to receive data collected from the dark web and structured; a Structured Data Database (SDD) connected with the data receiving module, the SDD configured to store the structured data; a Text Search and Analytic Engine (TSAE) connected with the SDD, the TSAE configured to enable advanced search and basic analysis in the structured data; a Knowledge Deduction Service (KDS) connected with the TSAE, the KDS configured to deeply analyze the collected data; the deep analysis comprises extracting insights regarding dark web surfers behavioral patterns and interactions; a Structured Knowledge Database (SKD) connected with the KDS, the SKD configured to store the deep analysis results; and an Alert Service connected with the TSAE and the SKD, the Alert Service configured to provide prioritized alerts based on the deep analysis.

Abstract: A method, system and computer program product for facilitating risk mitigation of information security threats. Data obtained from at least one tracked data source is analyzed for identifying at least one event related to a threat, to be stored in a database comprising date and time of each event identified, enabling generation of threat timeline comprising temporally ordered sequence of each event related to respective threat identified. Features selected using correlation between features from threat timelines in the database and labeling assigned using records of threat usage incidents are extracted from events in threat timeline for the threat which the at least one event related thereto being identified and based thereon a dynamic score indicating an estimated level of risk posed by the threat is calculated using at least one machine learning model for predicting threat usage during a time window defined, enabling risk mitigation based on outputted indication thereof.