Quantum Machine Learning Frameworks for Secure Next-Generation 6G Communication Networks and Intelligent Cyber-Physical Systems

Abstract

The transition from fifth-generation wireless systems to sixth-generation communication networks is expected to redefine global connectivity through ultra-low latency, native artificial intelligence, holographic communication, integrated sensing, and autonomous cyber-physical ecosystems. However, these capabilities also expand the attack surface of future networks and create unprecedented optimization complexity. Conventional machine learning methods have improved resource allocation, intrusion detection, and traffic forecasting, yet they may struggle with the scale, multidimensionality, and security demands of 6G environments. Quantum machine learning has emerged as a promising paradigm that combines quantum computational principles with data-driven intelligence to solve selected classes of problems more efficiently than classical approaches. This paper develops a quantum machine learning framework for secure 6G communication networks and intelligent cyber-physical systems. The study examines quantum-enhanced optimization for spectrum allocation, federated trust architectures for edge devices, anomaly detection for zero-trust environments, and secure orchestration for distributed autonomous systems. A comparative analytical model is presented in which classical AI architectures are benchmarked against hybrid quantum- classical pipelines. Results indicate that quantum-inspired and hybrid quantum methods can significantly improve decision efficiency, adaptive security response, and dynamic network management when deployed in suitable problem domains. The paper also evaluates implementation barriers including hardware noise, cost, talent shortages, interoperability, and regulatory uncertainty. The findings suggest that quantum machine learning can become a strategic pillar of future digital infrastructure when integrated responsibly with scalable communication engineering and cybersecurity governance.