SCIDS: A Soft Computing Intrusion Detection System
An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. This paper evaluates three fuzzy rule based classifiers for IDS and the performance is compared with decision trees, suppo...
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Published in | Distributed Computing - IWDC 2004 pp. 252 - 257 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
01.01.2004
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Series | Lecture Notes in Computer Science |
Online Access | Get full text |
ISBN | 9783540240761 3540240764 |
ISSN | 0302-9743 1611-3349 |
DOI | 10.1007/978-3-540-30536-1_29 |
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Summary: | An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. This paper evaluates three fuzzy rule based classifiers for IDS and the performance is compared with decision trees, support vector machines and linear genetic programming. Further, Soft Computing (SC) based IDS (SCIDS) is modeled as an ensemble of different classifiers to build light weight and more accurate (heavy weight) IDS. Empirical results clearly show that SC approach could play a major role for intrusion detection. |
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ISBN: | 9783540240761 3540240764 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-540-30536-1_29 |