Intrusion Detection System with the Data Mining Technologies

摘要：

Intrusion Detection Systems (IDSs) have become an efficient defense tool against network attacks since they allow network administrator to detect policy violations. However, traditional IDs are vulnerable to original and novel malicious attacks. Also, it is very inefficient to analyze from a large amount volume data such as possibility logs. In addition, there are high false positives and false negatives for the common IDSs. Data mining has been popularly recognized as an important way to mine useful information from large volumes of data which is noisy, fuzzy, and random. Thus, how to integrate the data mining techniques into the intrusion detection systems has become a hot topic recently. In this paper, we present the whole techniques of the IDS with data mining approaches in details.

关键词： Intrusion Detection Network Security Data Mining

作者: Wang Pu Wang Jun-qing

作者单位: Taiyuan University of Science and Technology Taiyuan 030024, China Beijing Normal University, zhuhai Zhuhai, Guangdong 519085, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Computer Networks(ICICN 2011)(2011年信息与计算机网络国际会议)

会议地点: 贵阳

会议语种:英文

页码: 490-492

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）