An efficient IDS using FIS to detect DDoS in IoT networks

Abstract

The growing Internet of Things (IoT) applications of today have brought numerous benefits to our lives. In addition, cyber-attacks are growing as a result of increasingly sophisticated and violent attacks. Detection systems that serve as security protection against emerging attacks are also being developed using machine learning techniques. However, many additional challenges continue to emerge as demand for Intrusion Detection System (IDS) deployment at the edge network, where resource-constrained devices exist, continues to increase. These devices require a database with a high level of accuracy for attack detection. This research provides a Fuzzy-based IDS for detecting DDOS attacks with over 99 percent accuracy rate that is deployable on edge computing using the IoT23 dataset.