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Evaluates a quantum-resistant trust framework in IoT networks, suggesting it enhances security against malicious activities.
The rapid development of the Internet of Things (IoT) has placed considerable pressure on both security and stability in heterogeneous, resource-constrained networks. In such dynamic environments, trust management is a central issue to determine which service providers can be trusted and to combat malicious activity. Although blockchain-based solutions have offered a means for decentralized, tamper-resistant trust management, most rely on classical cryptographic primitives, which are vulnerable to future quantum computing attacks. This study proposes a Quantum-Resistant Blockchain-Based Trust Management (QR-BCTM) framework in which Post-Quantum Cryptographic mechanisms, Permissioned Blockchain Platform, and Fog-assisted Trust Management architecture are combined and utilized in IoT networks. The framework introduces a quantum-aware trust computation model that combines behavioral trust, indirect recommendations, and a cryptographic assurance score quantifying each participant’s compliance with security requirements. Trust evidence is compressed to reduce blockchain storage and communication overhead, while the hierarchical fog-blockchain architecture offloads computationally intensive operations from resource-constrained IoT devices. The performance of the framework has been simulated in the presence of an adversary, including bad-mouthing, ballot-stuffing, on-off behavior, and identity attacks using a Sybil-type mechanism. Trust accuracy, false trust acceptance, communication overhead, and computation cost were measured, and a sensitivity analysis on the trust-weight parameters was performed. The simulation results suggest that QR-BCTM can enhance the accuracy of trust evaluation, mitigate the impact of malicious nodes, and remain scalable and efficient despite the existing cryptographic overhead. Post-quantum digital signatures and formal security analysis provide protection against quantum-era threats and attacks, while classical threats are mitigated through behavioral trust aggregation and recommendation filtering. In summary, QR-BCTM provides a scalable, simulation-validated and quantum-aware framework for trustworthy IoT network operation, offering practical guidelines for future deployment and prototyping.
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Al-Khasawneh et al. (2026) studied this question.
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