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 REFERENCES [1]. Wuling Ren, Jinzhu Cao, Xianjie Wu, “Application of Network Intrusion Detection Based on Fuzzy C-Means Clustering Algorithm”, IEEE, 2009 Third International Symposium on Intelligent Information Technology Application,
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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