Effect of Mutation and Crossover Probabilities on Genetic Algorithm and Signature Based Intrusion Detection System
Conventional methods of intrusion prevention like firewalls, cryptography techniques or access management schemes, have not provided complete protection to computer systems and networks from refined malwares and attacks. Intrusion Detection Systems (IDS) are giving the right solution to the current issues and became an important part of any security management system to detect these threats and will not generate widespread harm. The basic goal of IDS is to detect attacks and their nature that may harm the computer system. Several different approaches for intrusion detection have been reported in the literature. The signature based concept using genetic algorithm as features selection and, J48 as classifier to detect attack is proposed in this paper. The system was evaluated on KDD Cup 99, NSL-KDD and Kyoto 2006+ datasets.