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VULNERABILITY PROFILING BASED ON TIME SERIES ANALYSIS OF DATA STREAMS

机译:基于数据流时间序列分析的脆弱性分析

摘要

Various systems and methods are described for correlating technology choices with the risk of system vulnerabilities. A system captures and quantifies both observations of technology choices as well as the outputs certain outputs of internal choices and processes across a number of different organizations. A Bayesian estimate of vulnerability is imputed from the choices and observed use of vulnerable technology, further segmented by business type, revenue, and size. Differences between the observation of a particular organization and Bayesian expected value are measured and converted to vulnerability score, the vulnerability score embodying a point-in-time and longitudinal measure of organizational performance, including the likelihood of future compromise due to software vulnerabilities. The vulnerability score can then be further used to price risk, for example in a cyber insurance context.
机译:描述了用于使技术选择与系统漏洞风险相关联的各种系统和方法。系统捕获并量化对技术选择的观察以及对许多不同组织内部选择和过程的某些输出的输出。贝叶斯对脆弱性的估计是根据对脆弱技术的选择和观察使用得出的,并按业务类型,收入和规模进一步细分。测量对特定组织的观察结果与贝叶斯期望值之间的差异,并将其转换为漏洞评分,该漏洞评分体现了组织绩效的时间点和纵向度量,其中包括由于软件漏洞而导致将来受到损害的可能性。然后,漏洞评分可以进一步用于定价风险,例如在网络保险的情况下。

著录项

  • 公开/公告号US2019327259A1

    专利类型

  • 公开/公告日2019-10-24

    原文格式PDF

  • 申请/专利权人 JUNGLE DISK L.L.C.;

    申请/专利号US201815961541

  • 发明设计人 MICHAEL DEFELICE;

    申请日2018-04-24

  • 分类号H04L29/06;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 12:10:38

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