The Applications of Hidden Markov Models with States Depending on Observations to Computer Intrusion Detection

摘要：

In this paper, the problem of the applications of hidden Markov models with states depending on observations (HMMSDO) to computer intrusion detection is discussed. By introducing the relative entropy density divergence as a measure of the intrusion detection system (IDS) models, dependencies of the HMM and the HMMSDO are compared. Empirical results show that a HMMSDOs probability distribution conforms to the real probability distribution of the original audit data. A HMMSOO may perform better than a standard HMM in computer intrusion detection.

关键词： hidden Markov models with states depending on observations intrusion detection relative entropy density divergence

作者: Deqiang Chen

作者单位: Department of Information Science and Technology East China University of Political Science and Law Shanghai, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 741-743

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）