ZT-IoTrust demonstrates 92.5% attack detection in IoT, indicating quantum-resistant access control improves security.
Zero-trust security and federated learning have emerged as promising paradigms for edge computing, yet existing solutions struggle to balance security, privacy, and performance requirements effectively. This paper presents ZT-IoTrust, a zero-trust framework that integrates device-specific trust evaluation with quantum-resistant security mechanisms for secure IoT access control. The framework incorporates several key innovations: quantum-resistant cryptographic protocols based on lattice problems for long-term security, a dynamic federated trust evaluation system that continuously assesses individual IoT device behaviors, and an adaptive access control architecture that implements continuous verification principles while maintaining efficiency for resource-constrained environments. Experimental evaluation on CICIDS2017 and KDD Cup 1999 datasets demonstrates effectiveness across network-layer security metrics, achieving a 92.5% attack detection rate with 1.2% false positives and 0.5% privacy leakage. The device-specific trust evaluation mechanism achieves 93.0% accuracy within 12 federation rounds while maintaining 98.8% reliability under high concurrent loads. Performance analysis shows robust scalability, with response times remaining under 125 ms and throughput reaching 1250 requests per second as the system scales from 5 to 20 nodes. These results establish ZT-IoTrust as a practical solution for implementing zero-trust security in IoT environments, effectively balancing continuous verification with system performance requirements.
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Wang et al. (2025) studied this question.
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