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Attack Scenario Construction Based on Rule and Fuzzy Clustering.

Authors :
Yue Hao
Jiming Liu
Yu-Ping Wang
Yiu-ming Cheung
Hujun Yin
Licheng Jiao
Jianfeng Ma
Yong-Chang Jiao
Linru Ma
Lin Yang
Jianxin Wang
Source :
Computational Intelligence & Security (9783540308195); 2005, p328-333, 6p
Publication Year :
2005

Abstract

Correlation of intrusion alerts is a major technique in attack detection to build attack scenario. Rule-based and data mining methods have been used in some previous proposals to perform correlation. In this paper we integrate two complementary methods and introduce fuzzy clustering in the data mining method. To determine the fuzzy similarity coefficients, we introduce a hierarchy measurement and use weighted average to compute total similarity. This mechanism can measure the semantic distance of intrusion alerts with finer granularity than the common similarity measurement . The experimental results in this paper show that using fuzzy clustering method can reconstruct attack scenario which are wrecked by missed attacks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540308195
Database :
Supplemental Index
Journal :
Computational Intelligence & Security (9783540308195)
Publication Type :
Book
Accession number :
32885745
Full Text :
https://doi.org/10.1007/11596981_49