Security in IoT Devices against DDoS Attacks: Strategies and Mitigation Techniques

Abstract

The rapid growth of Internet of Things (IoT) deployments has increased the threat of Distributed Denial of Service (DDoS) attacks that use resource-constrained devices to disrupt critical services. This paper conducts a systematic literature review (SLR) following the PRISMA 2020 guidelines and synthesizes 62 studies published between 2023-2026 retrieved from IEEE Xplore, ACM, ScienceDirect, SpringerLink, Wiley, MDPI, and Scopus. The review classifies DDoS attack vectors, analyzes exploited IoT vulnerabilities, and evaluates mitigation strategies such as machine learning, blockchain, software-defined networking (SDN), and edge computing. Hybrid CNN-LSTM models can achieve up to 99.1% detection accuracies and federated learning is the fastest growing sub-area. It identifies key research gaps and a future roadmap prioritized.