OPTIMIZATION ALGORITHMS FOR INTRUSION DETECTION SYSTEM: A REVIEW - sadiq, sheren; Eesa, Adel Sabry (International Journal of Research -GRANTHAALAYAH, 2020)
With the growth and development of the Internet, the devices and the hosts connected to the Internet have become the target for attackers and intruders. Consequently, the integrity of systems and data has become more sophisticated. Meanwhile, many institutions suffer from money-losing or other losses due to attacks on computer systems. Accordingly, the detection of intrusion and attacks has become a challenge and a vital necessity at the same time. Many different methods were used to build intrusion detection systems (IDSs), and all these methods seek to a plus the efficiency of intrusion detection systems. This paper is a survey which tries to covers some of the optimization algorithms used in the field of intrusion detection in past ten years such as Artificial Bee Colony (ABC), Genetic Algorithm (GA), Cuttlefish Algorithms (CFA), and Particle Swarm Optimization (PSO). It is hoped that this review will provide useful insights about the intrusion detection literature and is a good source for anyone interested in applying one of the used optimization algorithms in the field of intrusion detection.