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

• Type: Journal
• Year: 2010
• Where: JAIHC
• Authors: Chet Langin, Shahram Rahimi
• Keywords: Future Research, Intrusion Detection, JAIHC 2010, Soft Computing