Author(s)

Alok Sharma, Sunil Pranit Lal

.

In this paper we introduced Tanimoto based similarity measure for host-based intrusions using binary feature set for training and classification. The k-nearest neighbor (kNN) classifier has been utilized to classify a given process as either normal or attack. The experimentation is conducted on DARPA-1998 database for intrusion detection and compared with other existing techniques. The introduced similarity measure shows promising results by achieving less false positive rate at 100% detection rate.

Intrusion Detection, ，kNN Classifier, Similarity Measure, Anomaly Detection, Tanimoto Similarity Measure

Sharma, A. and Lal, S. (2011) Tanimoto Based Similarity Measure for Intrusion Detection System. Journal of Information Security, 2, 195-201. doi: 10.4236/jis.2011.24019.