An immunity based network security risk estimation

被引:76
|
作者
Li, T [1 ]
机构
[1] Sichuan Univ, Dept Comp Sci, Chengdu 610065, Peoples R China
来源
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
artificial immune system; intrusion detection; network security; risk estimation;
D O I
10.1360/04yf0140
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunity-based model for the network security risk estimation (Insre). In Insre, the concepts and formal definitions of self, nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the self-tolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation, which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.
引用
收藏
页码:557 / 578
页数:22
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