A Unified Zero-Trust Framework Integrating Edge Intelligence, Blockchain, and Post-Quantum Cryptography for Secure 6G Cyber-Physical Systems

Abstract

The shift toward 6G networks brings advanced capabilities to Cyber-Physical Systems (CPS) and Internet of Everything (IoE) environments, but also introduces serious security concerns due to their highly distributed and dynamic characteristics. Existing perimeter-based security approaches are no longer sufficient to handle these challenges.
This study introduces a unified Zero-Trust security framework that combines Edge Intelligence, Blockchain, and Post-Quantum Cryptography (PQC) to achieve secure, efficient, and scalable communication. AI-driven Edge Intelligence, utilizing Deep Learning-based anomaly detection and adaptive AI techniques, enables rapid anomaly detection and adaptive threat mitigation at the edge. Blockchain technology supports decentralized authentication, ensures tamper-resistant record-keeping, and enables secure data exchange. In addition, PQC techniques, particularly lattice-based cryptography, are employed to protect systems from potential quantum computing threats.
The proposed framework is assessed using key metrics such as latency, communication overhead, detection performance, and resistance to cyberattacks including Distributed Denial of Service (DDoS) and Man-in-the-Middle (MITM). The results demonstrate higher detection accuracy, lower attack success rates, and improved data integrity compared to traditional methods.
Overall, this work offers a robust and future-ready security solution, supporting the safe deployment of emerging 6G applications such as smart grids, autonomous systems, and digital twin technologies.