An Enhancement of the Replacement Steady State Genetic Algorithm for Intrusion Detection

In these days, Internet and computer systems face many intrusions, thus for this purpose we need to build a detection or prevention security system. Intrusion Detection System (IDS) is a system used to detect attacks, Steady State Genetic Algorithm (SSGA) is applied to support IDS by supplying the rule pool with additional data, these data can be used in testing phase to detect the attacks. The main goal of this research is to enhance Replacement steady state genetic algorithm to detect intrusions. This enhancement has been achieved by comparing replacement methods. This research proved that the Triple Tournament Replacement is better than Binary Tournament Replacement to increase Detection Rate and there are no effects on False Positive Rate. In this research represent the results of DR equal 100% for three types of attack (DoS, Probe and R2T), and 53% for U2R.