Integrating AI, Blockchain, and Edge Computing for Zero-Trust IoT Security: A Comprehensive Review of Advanced Cybersecurity Framework

The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges due to the scale, complexity, and heterogeneity of interconnected devices. The current traditional centralized security models are deemed irrelevant in dealing with these threats, especially in decentralized applications where the IoT devices may at times operate on minimal resources. The emergence of new technologies, including Artificial Intelligence (AI), blockchain, edge computing, and Zero-Trust-Architecture (ZTA), is offering potential solutions as it helps with additional threat detection, data integrity, and system resilience in real-time. AI offers sophisticated anomaly detection and prediction analytics, and blockchain delivers decentralized and tamper-proof insurance over device communication and exchange of information. Edge computing enables low-latency character processing by distributing and moving the computational workload near the devices. The ZTA enhances security by continuously verifying each device and user on the network, adhering to the “never trust, always verify” ideology. The present research paper is a review of these technologies, finding out how they are used in securing IoT ecosystems, the issues of such integration, and the possibility of developing a multi-layered, adaptive security structure. Major concerns, such as scalability, resource limitations, and interoperability, are identified, and the way to optimize the application of AI, blockchain, and edge computing in zero-trust IoT systems in the future is discussed.