Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/4173 2019 2019 Assistant Professor, Department of Computer Science and Engineering (AIML), SRM Institute of Science and Technology, Ramapuram Campus, Chennai, Tamil Nadu, India M. M. Assistant Professor, Department of Electronics and Communication Engineering, Karpagam Institute of Technology, Coimbatore, Tamil Nadu, India R. Vijayakarthika Professor, Department of Artificial Intelligence and Data Science, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India M. Balakrishnan Associate Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India R. Sundar Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh, India T. Chithrakumar Assistant Professor, Department of Electronics and Communication Engineering, V.S.B College of Engineering Technical Campus, Coimbatore, Tamil Nadu, India Vaishnavi. V. The exponential growth of the Internet of Things (IoT) ecosystem has amplified concerns regarding data privacy, trust management, and cyber resilience in decentralized environments. Traditional perimeter-based security models are inadequate for heterogeneous IoT networks that operate across multiple domains. To address these challenges, this paper proposes a Blockchain-Augmented Zero Trust Architecture (BZTA) integrated with a hybrid intrusion detection mechanism for achieving secure, verifiable, and adaptive threat mitigation in decentralized IoT frameworks. The proposed BZTA employs blockchain-based identity verification to ensure device authenticity and policy-driven Zero Trust enforcement to validate every access request dynamically. A federated intrusion detection model built using Long Short-Term Memory (LSTM) and Graph Attention Networks (GAT) identifies anomalous communication patterns, while smart contracts facilitate tamper-proof logging and automated response coordination. The integration of Proof-of-Trust (PoT) consensus enhances scalability by minimizing latency during transaction validation. Experimental evaluations conducted on simulated IoT network datasets demonstrate a detection accuracy of 98.6%, false positive rate of 1.8%, and an average latency reduction of 22% compared to traditional IDS and standalone blockchain systems. The proposed BZTA framework effectively balances security, scalability, and interoperability, providing a resilient foundation for next-generation decentralized IoT infrastructures. 2025 2025 374 388 10.54216/JISIoT.170126 https://www.americaspg.com/articleinfo/18/show/4173