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Design of Network Attack Detection and Response Scheme based on Artificial Immune System in WDM Networks  

Yoo, Kyung-Min (전북대학교 컴퓨터공학과)
Yang, Won-Hyuk (전북대학교 컴퓨터공학과)
Kim, Young-Chon (전북대학교 IT정보공학부 영상정보신기술연구소)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.35, no.4B, 2010 , pp. 566-575 More about this Journal
Abstract
In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.
Keywords
AIS; Attack Detection; Immune System; WDM;
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