An Overview of Intrusion Detection Based on Data Mining Techniques

Abstract

Intrusion Detection System (IDS) is a vital component of any network in today's world of Internet. IDS are an effective way to detect different kinds of attacks in interconnected network. An effective Intrusion Detection System requires high accuracy and detection rate as well as low false alarm rate. Different Data Mining techniques such as clustering and classification are proving to be useful for analyzing and dealing with large amount of network traffic. This paper presents various data mining techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, to develop secure information systems.