DETECTION OF DDOS ATTACK IN IOT NETWORKS USING DEEP LEARNING TECHNOLOGIES

This research focuses on the Detection of Distributed Denial-of-Service (DDoS) Attacks in Internet of Things (IoT) Networks Using Deep Learning Technologies, with the aim of enhancing the ability of intelligent systems to identify malicious and abnormal activities within IoT environments. The research explores the application of deep learning techniques to analyze network traffic and distinguish normal behavior from activities associated with DDoS attacks, contributing to improved detection capabilities and stronger cybersecurity for IoT networks and connected devices. This research was conducted as Eng. Saja AlBayati’s Master’s graduation research, integrating cybersecurity, the Internet of Things, artificial intelligence, and deep learning to address one of the significant security challenges facing connected digital environments.