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信息系统脆弱性被利用概率计算方法
引用本文:柴继文,王胜,梁晖辉,胡兵,向宏.信息系统脆弱性被利用概率计算方法[J].重庆大学学报(自然科学版),2017,40(12):35-42.
作者姓名:柴继文  王胜  梁晖辉  胡兵  向宏
作者单位:国网四川省电力公司电力科学研究院, 成都 610072,国网四川省电力公司电力科学研究院, 成都 610072,国网四川省电力公司电力科学研究院, 成都 610072,重庆大学 信息物理社会可信服务计算教育部重点实验室, 重庆 400030,重庆大学 信息物理社会可信服务计算教育部重点实验室, 重庆 400030
基金项目:国网四川省电力公司科技项目(5219991351VR);国家自然科学基金资助项目(61472054)。
摘    要:针对现有信息系统风险评估工作中对脆弱性的评估未考虑各脆弱性间的相关性,评估结果受到较多人为主观因素的影响,提出"被利用难易程度"和"被选择概率"两个指标将现有对脆弱性的"被利用难易程度"评价转换为更为科学的"被利用概率"评价,并用贝叶斯网络的正向推理计算脆弱性节点的累积"被选择概率"。通过理论和实验分析,与相关的研究成果相比,提出的脆弱性被利用概率计算方法更准确、合理。

关 键 词:风险评估  脆弱性  贝叶斯网络  被利用概率
收稿时间:2017/7/14 0:00:00

A computing approach of information system vulnerability's exploited probability
CHAI Jiwen,WANG Sheng,LIANG Huihui,HU Bing and XIANG Hong.A computing approach of information system vulnerability's exploited probability[J].Journal of Chongqing University(Natural Science Edition),2017,40(12):35-42.
Authors:CHAI Jiwen  WANG Sheng  LIANG Huihui  HU Bing and XIANG Hong
Institution:State Gid Sichuan Electric Power Research Institute, Chengdu 610072, P. R. China,State Gid Sichuan Electric Power Research Institute, Chengdu 610072, P. R. China,State Gid Sichuan Electric Power Research Institute, Chengdu 610072, P. R. China,Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing 400030, P. R. China and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing 400030, P. R. China
Abstract:The evaluation results are impacted by many subjective factors since the existing risk assessment for information systems does not take the correlation of vulnerabilities into account. By combining two assessment vectors, i.e. access complexity and chosen probability, we transfer the so called "accessed complexity" evaluation method into an "exploited probability" evaluation approach, and use Bayesian networks'' forward inference to accumulation each of vulnerability''s chosen probability. Theoretical and experimental analysis show that the proposed "exploited probability" evaluation method is more accurate and reasonable than associated existing research work.
Keywords:risk assessment  vulnerability  Bayesian network  exploited probability
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