Post-Quantum Federated IoT Security: A Survey with QoE Perspectives

The intensely growing Internet of Things (IoT) has brought up critical issues regarding security, privacy, scalability and Quality of Experience (QoE). Current measures to be used, including deep learning-based intrusion detection, blockchain-based security, and federated learning are independent of each other and do not offer a cohesive structure, resulting in fragmented and inefficient protection systems. The paper provides an extensive overview of the IoT security strategies through the analysis and synthesis of intrusion detection systems, blockchain technologies, federated learning models and QoE optimization methods. The paper is a systematic review of current developments providing insights into the main research gaps such as the need to integrate it, the absence of support of post-quantum cryptography, insufficient privacy assurances in federated learning, and a deficiency of connections between security and QoE. The results point to the idea that the existing models are not scalable, do not have a real-time level of flexibility, and can be targeted by future quantum threats. The survey identifies the necessity of integrated, post-quantum, federated and QoE intelligent IoT security. The results of this paper can be used in the design of safe and user-friendly IoT systems in smart cities, healthcare, and future 5G/6G communication infrastructure.