The Optimization and Enhancement of Network Intrusion Detection through Fuzzy Association Rules

Abstract

The objective of this paper is to analyze network security using a modification of fuzzy logic and association rule data mining base on genetic network programming (GNP) evaluations. The application of fuzzy set theory together with GNP combined will increase the ability to detect threats on a computer network or the Internet. The proposed method is an extension of the intrusion detection method so that it can detect and distinguish known and unknown normal intrusion using the GNP workflow method to obtain the required number of rules. In the experiment, 10% data sets of KDD cup 99 data sets were used to teach and test the developed system's performance. The test results from similar algorithms were then compared.