Unsupervised anomaly intrusion detection using ant colony clustering model

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 optimal 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.