Abstrato

A Study of Network Intrusion Detection by Applying Clustering Techniques

Subaira.A.S, Anitha.P

In information system, security has remained one hard line area for computers as well as networks. In information protection, Intrusion Detection System (IDS) is used to safeguard the data confidentiality, integrity and system availability from various types of attacks. Data mining is an efficient artifice applied to intrusion detection to ascertain a new outline from the massive network data as well as it used to reduce the strain of the manual compilations of the normal and abnormal behavior patterns. This piece of writing reviews the present state of data mining clustering techniques to implement an intrusion detection system such as, Partitioning methods, Hierarchical methods, Model based clustering methods and their various types.