An Intrusion Detection System Approach with Genetic Algorithm and Fuzzy Logic for Implementation of Software Networks

Abstract

An intrusion detection system (IDS) is a device or software application that awnings network or system activities for malicious activities or policy violations and produces reports to a management station. IDS come in many of flavours and approach the goal ofdetecting suspicious traffic in different ways.These days Intrusion Detection System (IDS) which is defined as a solution of system security isemployed to identify the abnormal activities in a computer system or network. So far different approaches have beenutilized in intrusion detections, but unluckily any of the systems is not entirely ideal. Hence, the hunt of improvedmethod goes on. In this progression, here I am giving a survey of an Intrusion Detection System (IDS), by applying geneticalgorithm (GA) and fuzzy logic to efficiently detect various types of the intrusive activities within a network.Different soft computing based approaches have been proposed to detect computer network attacks. This paper presents a survey ofgenetic algorithm (GA) based approach to network intrusion detection. The genetic algorithm is employed to derive a set of classification rules from network audit data, and the support-confidence framework is utilized as fitness function to judge the quality of each rule.