Data Mining Techniques for Intrusion Detection A Review

Abstract: With the dramatically development of internet, Security of network traffic is becoming a major issue of computer network system. Attacks on the network are increasing day-by-day. The most publicized attack on network traffic is considered as Intrusion. Intrusion detection system has been used for ascertaining intrusion and to preserve the security goals of information from attacks. Data mining techniques are used to monitor and analyze large amount of network data & classify these network data into anomalous and normal data. Since data comes from various sources, network traffic is large. Data mining techniques such as classification and clustering are applied to build Intrusion detection system. An effective Intrusion detection system requires high detection rate, low false alarm rate as well as high accuracy. This paper presents the review on IDS and different Data mining techniques applied on IDS for the effective detection of pattern for both malicious and normal activities in network, which helps to develop secure information system.

Keywords: Intrusion Detection System; Anomaly Detection; Misuse Detection; Data mining; Clustering; Classifications