Analyzing host security using D-S evidence theory and multisource information fusion

被引:35
作者
Li, Yuanzhang [1 ]
Yao, Shangjun [1 ,2 ]
Zhang, Ruyun [3 ]
Yang, Chen [1 ]
机构
[1] Beijing Inst Technol, Sch Comp Sci & Technol, Beijing 100081, Peoples R China
[2] Guangzhou Univ, Inst Artificial Intelligence & Blockchain, Guangzhou, Peoples R China
[3] Zhejiang Lab, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
blockchain; D‐ S evidence theory; host security analysis; machine learning; privacy protection; NETWORK; CLASSIFICATION; SYSTEMS;
D O I
10.1002/int.22330
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Security monitoring and analysis can help users to timely perceive threats faced by the host, thereby protecting and backup data and improving the host's security status. In the research domain of host security analysis, many feasible solutions have been proposed. However, real-time performance and accuracy still need improvement. This paper proposes a host security analysis method based on Dempster-Shafer (D-S) evidence theory. It adopts three models of support vector regression, logistic regression, and K-nearest neighbor regression, as sensors for multisource information fusion. Multiple sensors perform security analysis on the host, respectively, and use the analysis results as evidence of D-S evidence theory. Experiments show that the proposed method provides effective security protection for the host in terms of absolute error, root mean square error, and the average absolute percentage error.
引用
收藏
页码:1053 / 1068
页数:16
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