Optimizing Intrusion Detection with Bayesian Optimization in Reactive Intrusion Detection Systems (BO-RIDS) for Enhanced Security Performance
摘要
Network security depends heavily on the “Intrusion Detection Systems” (IDS) because they provide real-time detection of security attacks. A reactive IDS serves two primary functions including intrusion detection and automated protection system activation for risk reduction. Traditional IDS systems face operational challenges during the process of combining accurate intrusion detection with reduced false alarms at shorter response times. The article presents BO-RIDS as an upgraded “Reactive Intrusion Detection System” (RIDS) that uses “Bayesian Optimization” (BO) technology to overcome preceding detection system challenges. Bayesian Optimization enables the system to progressively develop against new network threats thus improving detection abilities multiple times. The optimization process within determination changes detection boundaries as well as detection methods and reaction approaches to enhance intrusion detection performance. System adaptability to changing network attack protocols gives this method your security protection needs that can evolve based on new attack patterns.