Applicability of clustering techniques on masquerade detection

In masquerade attack, attacker impersonates legitimate user. Most of the masquerade detection techniques done so far are based on supervised learning techniques. But here in this paper masquerade detection based on unsupervised learning techniques are used. Various clustering algorithms used are K-Means, K-Medoid, Agglomerative clustering algorithm and DBSCAN. A comparative study is done based on the detection capability of these four clustering algorithms. The experiment is conducted on Schonlau data set [1]. From the experiment it was found that K-Medoid algorithm, agglomerative clustering algorithm and DBSCAN algorithm outperforms K-means clustering.