- 专利标题: Complex application attack quantification, testing, detection and prevention
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申请号: US16963105申请日: 2019-01-18
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公开(公告)号: US11190538B2公开(公告)日: 2021-11-30
- 发明人: Anand Paturi , Srinivas Mukkamala
- 申请人: RiskSense, Inc.
- 申请人地址: US NM Albuquerque
- 专利权人: RiskSense, Inc.
- 当前专利权人: RiskSense, Inc.
- 当前专利权人地址: US NM Albuquerque
- 代理机构: Peacock Law P.C.
- 代理商 Justin R. Jackson
- 国际申请: PCT/US2019/014342 WO 20190118
- 国际公布: WO2019/144039 WO 20190725
- 主分类号: H04L9/00
- IPC分类号: 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
摘要:
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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