PDFAbstract: Clustering of attack patterns is used in intrusion detection and discussed in this paper. Fuzzy CMeans (FCM) is a popular method for clustering; the performance of FCM is depends to its parameters radically. In this paper, performance of FCM is evaluated with some Validity Indices and represented in a multi-objective optimization problem. Multi-Objective Simulated Annealing (AMOSA) has high power to solve multi-objective optimization problems, so it is used in this paper to tune the parameters of FCM.
Keywords: Intrusion Detection, Clustering, FCM, Multi-Objective Optimization, AMOSA
Cite this paper
Seyed Mahmood Hashemi, Jingsha He. (2016) Tuning FCM Parameters with AMOSA. International Journal of Computers, 1 , 56-61
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