Intrusion detection system with the data mining technologies

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.