Title :
Improved Method for Network Danger Evaluation Based on Immunology Principle
Author :
Yang, Jin ; Jin, Peng ; Hong, YanWei ; Luo, Gang
Author_Institution :
Dept. of Comput. Sci., LeShan Normal Univ., Leshan, China
Abstract :
This paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. An improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. A new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. Additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. The experimental results show that the proposed model is a good solution for network security evaluation.
Keywords :
security of data; antibody concentration; clone selection; hierarchical management framework; immunological surveillance; immunology principle; intrusion detection; network danger evaluation; network security evaluation; self-tolerance; Artificial immune systems; Biological system modeling; Cloning; Computer networks; Computer science; Detectors; Immune system; Intrusion detection; Protocols; Surveillance; Artificial Immune system (AIS); Intrusion Detection System; Network Security;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.169