Intrusion Detection using unsupervised learning
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 5
Abstract
Clustering is the one of the efficient datamining techniques for intrusion detection. In clustering algorithm kmean clustering is widely used for intrusion detection. Because it gives efficient results incase of huge datasets. But sometime kmean clustering fails to give best result because of class dominance problem and no class problem. So for removing these problems we are proposing two new algorithms for cluster to class assignment. According to our experimental results the proposed algorithm are having high precision and recall for low class instances.
Authors and Affiliations
Kusum bharti , Sanyam Shukla , Shweta Jain
Keywords
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