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http://dx.doi.org/10.5391/JKIIS.2003.13.2.169

Adaptive Intrusion Detection Algorithm based on Artificial Immune System  

Sim, Kwee-Bo (중앙대학교 전자전기공학부)
Yang, Jae-Won (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.13, no.2, 2003 , pp. 169-174 More about this Journal
Abstract
The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.
Keywords
positive selection; negative selection; positive detector; negative detector; hybrid detector;
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