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SCIDS: A soft computing intrusion detection system
- Authors
- Abraham, A.; Jain, R.; Sanyal, S.; Han, S.Y.
- Issue Date
- Dec-2004
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- DISTRIBUTED COMPUTING - IWDC 2004, PROCEEDINGS, v.3326, pp 252 - 257
- Pages
- 6
- Journal Title
- DISTRIBUTED COMPUTING - IWDC 2004, PROCEEDINGS
- Volume
- 3326
- Start Page
- 252
- End Page
- 257
- ISSN
- 0302-9743
1611-3349
- Abstract
- 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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