A Novel Network Security Evaluation System Based on Immune Principle

One significant feature of the theory immunology is the ability to adapt to changing environments and dy- namically learning continuously. Inspired by the the- ory of artificial immune systems (AIS), a novel model of Agents of Network Danger Evaluation is presented. The concepts and formal definitions of immune cells are given, and dynamically evaluative equations for self, antigen, immune tolerance, mature-lymphocyte lifecycle and immune memory are presented, and the hierarchical and distributed management framework of the proposed model are built. Furthermore, the idea of dynamic immunological surveillance period is ap- plied for enhancing the self-learning ability to adapt continuously variety environments. The experimental results show that the proposed model has the features of real-time processing that provide a good solution for network surveillance.