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JAIHC
2010

Soft computing in intrusion detection: the state of the art

8 years 5 months ago
Soft computing in intrusion detection: the state of the art
The state of the art is explored in using soft computing (SC) methods for network intrusion detection, including the examination of efforts in ten specific areas of SC as well as consecutive, ensemble, and hybrid combinations. Numerous comparisons of these methods are listed followed by a recommendation for future research. This paper can be used as a reference of strategies, and as a resource for planning future research. Keywords Artificial immune systems (AIS) Á Artificial neural networks (ANN) Á Bayes reasoning Á Decision trees (DT) Á Dempster–Shafer (D–S) Á Ensemble combinations Á Evolutionary computing (EC) Á Feature selection Á Fuzzy reasoning Á Hidden Markov model (HMM) Á Hybrid combinations Á Intrusion detection systems (IDS) Á Self-organizing maps (SOM) Á Soft computing Á State of the art Á Swarm intelligence
Chet Langin, Shahram Rahimi
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where JAIHC
Authors Chet Langin, Shahram Rahimi
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