The Ids Security Challenge Solutions Offered by Metaheuristic Optimization

The concern of this paper is to analyze the potential solutions offered by metaheuristic optimization for intruder detection systems, which have become standard due to their use throughout industries.Most recent trends have caused a large influx of potentially vulnerable devices, leading to the increasing challenge of properly detecting what constitutes a false positive or true positive detection.The aim of the research is twofold: a) to identify aspects of the intrusion detection system that can be improved b) to identify methods via which this improvement can be achieved.The methodology of meta-research includes a comparative analysis of the systems based on secondary sources (papers published in prestigious journals) and accompanying references to the theoretical and industrial aspects.The first step is to analyze the optimization techniques, chosen as the case studies, such as the genetic algorithm, firefly algorithm, chimp optimization algorithm, etc.In the next step, the paper diagnoses the security challenges faced by modern IDS solutions and discusses the proposed improvement (and optimizations) offered by the previously mentioned metaheuristic optimizations.