Study of Data Mining Based Approaches For Network Intrusion Detection System

Abstract

In the current era, there is ample knowledge in using Internet in social networks (such as instant messaging, video conferencing, etc.), the field of healthcare, various areas related to electronic commerce, banking and services several other fields. As computer systems based on the network plays an ever more important in modern society once they have become the target of our enemies and criminals. Therefore, we must find the best way to protect our systems. The security of a computer system is compromised during an intrusion occurs. Intrusion can be defined as “a set of actions that aim to compromise the integrity, confidentiality or availability of a resource,” for example, illegally obtain superuser privileges to attack and make out of the system (ie, Denial of Service), etc. The purpose of this document is to provide a study of some works that use data mining techniques to detect intrusions and answer some technical questions. An advance effective idea is discussed in the chapter that will detect intruders in a data storage perspective and integrate data mining and online analytical processing (OLAP) for the purpose of intrusion detection.