信息熵理论与入侵检测聚类问题研究

Study on Clustering Problem for Intrusion Detection with Information Entropy

将信息熵理论应用到入侵检测聚类问题中,实现了一种启发式入侵检测聚类算法HBEC,它能递增地处理巨大的网络连接记录数据库.通过实验证明了算法HBEC对解决入侵检测问题是有效的,并且具有很强的增量挖掘能力.

This paper applies the theory of information entropy to the clustering problem for intrusion detection, and realizes the heuristic algorithm HBEC to solve the clustering problem for intrusion detection, which can deal with the database with large connection records incrementally. The experiment shows that HBEC is effective to resolve the intrusion detection problem and has the strongly incremental mining ability.