Tanimoto Based Similarity Measure for Intrusion Detection System

• 作者: Alok Sharma Sunil Pranit Lal
• 来源期刊: 信息安全(英文)
• 学科: 工学
• 关键词: INTRUSION DETECTION kNN CLASSIFIER SIMILARITY MEASURE Anomaly DETECTION Tanimoto SIMILARITY MEASURE
• 年，卷（期）: 2011,（4）
• 页码范围: 195-201
• 页数: 7页
• 分类号: TP39

摘要

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.