Comparative Analysis of an AI-enabled State-of-the-Art Models for the Detection of DDoS Attacks on IoT Devices

With technological advancement, Distributed Denial of Service (DDoS) attacks are gaining momentum in IoT networks. DDoS attacks are widely spreading on IoT devices since they have limited resources (memory) and no efficient security models. Different security measures are available to protect IoT devices from attacks. Some of these are firewalls, Intrusion detection systems, etc. Recently, researchers have utilized Artificial Intelligence for early detection of attacks due to its capability of detecting menaced attacks and, hence, boosting security. In this paper, a rigorous survey of different AI-enabled state-of-the-art models for detecting DDoS Attacks was done, and the future direction and scope of improvement for early Detection of DDoS attacks on IoT devices were highlighted.