摘要
According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunitybased 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 selftolerance, 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.
According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunitybased 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 selftolerance, 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.
基金
the National Natural Science Foundation of China(Grant No 60373110)
Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No 20030610003)
New Century Excellent Expert Program of Ministry of Ed ucation of China(Grant No 20030610003)
the Innovation Foundation of Sichuan University(Grant No.2004CF10).
