Securing the Next-Generation IoT: An Integrated Security Framework with AI, Blockchain, and Edge Computing

The Internet of Things (IoT) connects billions of devices across diverse domains, delivering transformative services but also introducing significant security challenges. While individual technologies like AI and blockchain have been applied to IoT security, the key challenge lies in creating a synergistic and scalable framework where these components work together to provide multi-layered defense without introducing prohibitive overhead. This paper presents an integrated IoT security framework that combines foundational techniques (encryption, authentication, access control) with advanced strategies (artificial intelligence for threat detection, blockchain for trust management, and edge computing for real-time protection). We propose a multi-layer architecture that secures IoT devices from the device level to the cloud, incorporating a blockchain-based trust network and AI-driven anomaly detection at the network edge. The framework is evaluated through simulation and a case study, demonstrating a 62.6% reduction in authentication latency compared to traditional PKI approaches, an 85% improvement in threat response time, and 96.8% threat detection accuracy. We discuss how our approach builds on state-of-the-art IoT security research and addresses current gaps such as device heterogeneity and lack of standardization. The paper concludes that by unifying encryption, robust access control, blockchain, AI, and edge intelligence, next-generation IoT ecosystems can achieve a significantly higher level of security and trust.