Analyzing Soft Computing based Intrusion Detection Systems

Abstract

With the growth of Internet both in its importance and size, network security is also become vital. Intrusion Detection System is one of
the important components here. Intrusion Detection Systems based on Soft Computing are currently attracting considerable interest from
research community. Characteristics of Soft Computing, such as adaptation, fault tolerance, and error resilience in the face of noisy information,
fit the requirements of building a good intrusion detection model. Typically Soft Computing algorithms learn from human knowledge and mimic
human skills. Here we have analyzed the application of Soft Computing to the problem of intrusion detection. In this work primarily we have
focused on Genetic Algorithm and Neural Network. Such evolutionary techniques are tested effectively using KDD Cup 99 dataset.

Keywords: Network Security, Intrusion Detection System, Soft Computing, Genetic Algorithm, Neural Network