Blockchain-artificial Intelligence Integration for Securing IoT Networks in Smart Cities and Critical Infrastructure

Abstract

The fast growth of Internet of Things (IoT) systems in smart cities and critical infrastructure has brought a great threat to cybersecurity, such as data breaches, distributed denial-of-service attacks, and centralised systems, which are a critical vulnerability. This work is a systematic review of the Blockchain-vitro artificially intelligent models of optimally securing IoT in smart infrastructure settings. This review will adhere to the PRISMA 2024 approach to locate, filter and synthesise peer-reviewed articles in large scientific databases since 2015. 1,384 records were found, and 43 studies were included in the final inclusion criteria. The architectural models, artificial intelligence methods, blockchain consensus mechanisms, and system performance metrics included in the analysis are able to detect scalability and interoperability. The results indicate that blockchain can be used to improve IoT security with the help of decentralisation, cryptographic integrity, and tamper-resistant data management, whereas artificial intelligence can be used to enhance adaptive threat detection by utilising anomaly detection, predictive analytics, and behavioural modelling. Nevertheless, difficulties exist such as computational overhead, lack of interoperability, regulatory compliance and inadequate real-world deployment validation. The review finds that blockchain-AI integrated systems have great potential to secure large-scale IoT infrastructures, but further studies are required to enhance scalability, alignment with regulations, and operational deployment. The research is relevant to the body of literature because it offers a synthesis of blockchain-AI cybersecurity frameworks in a comprehensive manner and establishes some of the research gaps that need to be filled in future smart infrastructure security systems.