Invention Grant
- Patent Title: Complex application attack quantification, testing, detection and prevention
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Application No.: US16963105Application Date: 2019-01-18
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Publication No.: US11190538B2Publication Date: 2021-11-30
- Inventor: Anand Paturi , Srinivas Mukkamala
- Applicant: RiskSense, Inc.
- Applicant Address: US NM Albuquerque
- Assignee: RiskSense, Inc.
- Current Assignee: RiskSense, Inc.
- Current Assignee Address: US NM Albuquerque
- Agency: Peacock Law P.C.
- Agent Justin R. Jackson
- International Application: PCT/US2019/014342 WO 20190118
- International Announcement: WO2019/144039 WO 20190725
- Main IPC: H04L9/00
- IPC: H04L9/00 ; H04L29/06 ; G06N5/04 ; G06F16/958 ; G06F21/54 ; G06Q30/00 ; H04L29/08 ; G06N5/02 ; G06N20/00 ; G06F16/901 ; G06Q10/10 ; G06K9/62 ; G06N7/00 ; G06F21/57

Abstract:
An apparatus and method for cyber risk quantification calculated from the likelihood of a cyber-attack on the target enterprise and/or cyber ecosystem based on its security posture. The cyber-attack likelihood can be derived as a probability-based time-to-event (TTE) measure using survivor function analysis. The likelihood probability measure can also be passed to cyber risk frameworks to determine financial impacts of the cyber-attacks. Embodiments of the present invention also relate to an apparatus and method (1) to identify and validate application attack surfaces and protect web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks; and/or (2) that protects web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks. This can include implementing an intelligent learning loop using artificial intelligence that creates an ontology-based knowledge base from application request and response sequences. Stochastic probabilistic measures are preferably applied to a knowledge base for predicting malicious user actions in real time.
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