Intrusion Detection System based on Learning Fuzzy Rules and Membership Functions using Genetic Algorithms
Ezat Soleiman, Abdelhamid Fetanat · International Journal of Computer Applications · 2013
With the rapid expansion of Internet in recent years, computer systems are facing increased number of security threats.Despite numerous technological innovations for information assurance, it is still very difficult to protect computer systems.Therefore, unwanted intrusions take place when the actual software systems are running.Different soft computing based approaches have been proposed to detect computer network attacks.Hybrid methods proved more effective and accurate, this paper tries to introduce how to use dynamic fuzzy rules and genetic algorithm in intrusion detection systems.