A Novel IDS System based on Hedge Algebras to Detect DDOS Attack in IoT Systems

Abstract

In recent years, we have experienced IoT solutions' rapid and beneficial development throughout all aspects of life. In addition to the apparent advantages, the increased number and variety of devices have resulted in more security issues. The DDOS attack, which originates from a broad range of sources and is a significant challenge for IoT systems, is one of the most prevalent but devastating attacks. IoT devices are typically simple and have few computing resources, which puts them at risk of being infected and attackers. IDS intrusion detection systems are considered superior protection against DDOS attacks. Therefore, the IDS system attracts many researchers and implements intelligent techniques such as machine learning and fuzzy logic to detect these DDOS attacks quickly and precisely. Along with the approach of intelligent computation, this study presents a novel technique for detecting DDOS attacks based on hedge algebra, which has never been implemented on IDS systems. We use the PSO swarm optimization algorithm to optimize the proposed model's parameters for optimized performance. Our experiment on the IoT-23 dataset shows that the proposed model's accuracy and performance metrics for DDOS attack detection are better than those proposed by other previous authors.