Title :
Network Intrusion Active Defense Model Based on Artificial Immune System
Author :
Zhang, Cheng ; Zhang, Jing ; Liu, Sunjun ; Liu, Yintian
Author_Institution :
Sch. of Comput. Sci. & Eng., Xi´´an Univ. of Technol., Xi´´an
Abstract :
Based on artificial immune theory, a new model of active defense for analyzing the network intrusion is presented. Dynamically evaluative equations for self, antigen, immune tolerance, mature-lymphocyte lifecycle and immune memory are presented. The concepts and formal definitions of immune cells are given, the hierarchical and distributed management framework of the proposed model are built. Furthermore, the idea of biology immunity is applied for enhancing the self-adapting and self-learning ability to adapt continuously variety environments. The experimental results show that the proposed model has the features of real-time processing, self-adaptively, and diversity, thus providing a good solution for network surveillance.
Keywords :
artificial immune systems; security of data; surveillance; unsupervised learning; antigen; artificial immune system; biology immunity; immune cells; immune memory; immune tolerance; mature-lymphocyte lifecycle; network intrusion active defense model; network surveillance; self-adapting; self-learning; Artificial immune systems; Biological system modeling; Cells (biology); Cloning; Computer networks; Consumer electronics; Immune system; Intrusion detection; Semiconductor optical amplifiers; Service oriented architecture; Artificial Immune System; Intrusion Detection System; Network Security;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.782