In this paper, we present an efficient and biologically inspired clustering model for anomaly intrusion detection. The proposed model called Ant Colony Clustering Model (ACCM) that improves existing ant-based clustering model in searching for op-timal clustering heuristically. Experimental results on KDD-Cup99 benchmark data show that ACCM is effective to detect known and unseen attacks with high detection rate and low false positive rate.
CITATION STYLE
Tsang, W., & Kwong, S. (2005). Unsupervised anomaly intrusion detection using ant colony clustering model. In Advances in Soft Computing (pp. 223–232). Springer Verlag. https://doi.org/10.1007/3-540-32391-0_30
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