A Survey on Efficient Data Mining Techniques for Network Intrusion Detection System (IDS)

Abstract: Network security technology has become crucial in protecting government and industry computing infrastructure. Modern intrusion detection applications facing complex problems. These applications has to be require reliable, extensible, easy to manage, and have low maintenance cost. In recent years, data mining-based intrusion detection systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in the design and implementation of production quality IDSs. Instrumenting components such as data transformations, model deployment, cooperative distributed detection and complex engineering endeavor. The IDS used data mining techniques for the network security, because to protect the network from various attacks and malicious traffic. This survey paper describes the Data mining approaches which are used to the detect intrusion in a network.

Keywords: Anomaly detection, Data mining, Intrusion detection system, Misuse detection.