Distributed Denial of Service Attack in the Internet of Things

Abstract

The Internet of Things (IoT) connects intelligent devices without human intervention, enabling applications like smart homes and healthcare. However, its rapid expansion introduces significant security challenges, particularly in the form of Distributed Denial of Service (DDoS) attacks. These attacks exploit IoT devices to flood networks, disrupting services and compromising availability. Due to their distributed nature, DDoS attacks are difficult to detect and mitigate, making them a critical research focus. This paper provides a comprehensive analysis of DDoS attacks in IoT, covering their mechanisms, types (e.g., SYN flood, UDP flood), and vulnerabilities in IoT ecosystems. Additionally, it reviews detection and mitigation techniques, including artificial intelligence, blockchain, and machine learning, and proposes a hybrid AI-blockchain framework for enhanced defense. The study highlights current gaps and outlines future directions for securing IoT networks against evolving DDoS threats.

Keywords:

IoT, DDoS, attack detection, security, mitigation techniques

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