Article citationsMore>>

W. Wang, X. Guan and X. Zhang, “A Novel Intrusion Detection Method Based on Principle Component Analy- sis in Computer Security,” Proceedings of the Interna- tional IEEE Symposium on Neural Networks, Dalian, Lecture Notes in Computer Science, Vol. 3174, No. 2004, 2004, pp. 657-662. doi:10.1007/978-3-540-28648-6_105

has been cited by the following article:

• TITLE: Tanimoto Based Similarity Measure for Intrusion Detection System

  AUTHORS: Alok Sharma, Sunil Pranit Lal

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

  JOURNAL NAME: Journal of Information Security, Vol.2 No.4, October 24, 2011

  ABSTRACT: 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.