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A CBR Engine Adapting to IDS.

Authors :
Yue Hao
Jiming Liu
Yu-Ping Wang
Yiu-ming Cheung
Hujun Yin
Licheng Jiao
Jianfeng Ma
Yong-Chang Jiao
Lingjuan Li
Wenyu Tang
Ruchuan Wang
Source :
Computational Intelligence & Security (9783540308195); 2005, p334-339, 6p
Publication Year :
2005

Abstract

CBR is one of the most important artificial intelligence methods. In this paper, it is introduced to detect the variation of known attacks and to reduce the false negative rate in rule based IDS. After briefly describes the basic process of CBR and the methods of describing case and constructing case base by rules of IDS, this paper focuses on the CBR engine. A new CBR engine adapting to IDS is designed because the common CBR engines cannot deal with the specialties of intrusion cases in IDS. The structure of the new engine is described by class graph, and the core class as well as the similarity algorithm adopted by it is analyzed. At last, the results of testing the new engine on Snort are shown, and the validity of the engine is substantiated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540308195
Database :
Supplemental Index
Journal :
Computational Intelligence & Security (9783540308195)
Publication Type :
Book
Accession number :
32885746
Full Text :
https://doi.org/10.1007/11596981_50