ABSTRACT
Privacy preservation tools using particle swarm optimization (PSO) is one of the most common metaheuristics swarm intelligence algorithms [1]. It has been widely used for a large portion of optimization problems, as its implementation is scalable, robust, flexible, and simple [2]. It also strikes a balance between exploratory and exploitative behavior, to provide a high quality of results. On the other hand, intrusion detection is a hot topic, since the security of the data is a critical issue in today’s life. Thus, the application of intrusion detection, considering the classification algorithms that are optimized by PSO, is covered extensively in the literature. In this chapter, several approaches combining classification techniques with PSO for intrusion detection are reviewed and summarized. A general presentation of the PSO algorithm is provided. PSO-based techniques for intrusion detection are introduced and detailed. The most common datasets and evaluation measures are discussed. Finally, a summary discussion of PSO-based intrusion detection techniques is provided, along with possible directions and insights.
