The Security Landscape of AI-Driven IoT and Blockchain Systems: A Comprehensive Review

Abstract

The intersection of Artificial Intelligence (AI), the Internet of Things (IoT) and Blockchain has become a revolutionary paradigm that allows the implementation of intelligent automation, decentralized trust, and secure data storage in a variety of areas. This survey provides a detailed review of the underlying principles, integration models, security issues, and emerging solutions at the intersection of these technologies. AI complements IoT systems with more advanced analytics, predictive intelligence, and autonomous decision-making, whereas the IoT serves as a source of real-time data needed to train and deploy AI models. Blockchain complements both technologies by providing immutability, transparent transactions, and secure identity management. The use of these technologies, however, comes with complex security risks, such as adversarial attacks on AI models, IoT device attacks, and blockchain-specific threats, such as smart contract vulnerabilities and consensus-based attacks. The survey identifies cross-domain risks that occur when these systems are used together and assesses existing solutions that utilize AI-driven security, trust systems based on blockchain, and cryptographic privacy-preserving methods. It also addresses practical applications in healthcare, smart cities, Industry 4.0, and autonomous transportation, showing the relevance of secure integration. Lastly, the paper presents the open research issues of scalability, privacy, interoperability, and sustainability, and describes the future research directions for building resilient and trustworthy AI-IoT-Blockchain ecosystems.