AANtID: an alternative approach to network intrusion detection

Abstract

Information that is not properly secured has the tendency of being vulnerable to intrusions and threats. Security has become not just a feature of an information system, but the core and a necessity especially the systems that communicate and transmit data over the Internet for they are more susceptible to intrusions and threats. This work aims at presenting an approach to intrusion detection. This paper presents an Intrusion Detection System (IDS) using Genetic Algorithm (GA). GA was chosen because it has been proven to efficiently detect different types of intrusions. GA parameters and the evolution process are discussed in detail. The DARPA 1998 dataset was used to implement and measure the performance of the system. The result that was obtained showed that specific Class of IP addresses were more susceptible to intrusions and threats.

Keywords: Intrusion, Genetic Algorithm, detection, Security, DARPA dataset