Symbiotic Communication improves spectrum efficiency and sustainability in 6G through cooperative resource exchange among heterogeneous devices. Its integration with blockchain enables Symbiotic Blockchain Networks (SBNs), which provide decentralized and immutable agreements for symbiotic services. However, these systems assume that off-chain wireless observations are correct. This assumption is unreliable in adversarial and noisy PHY-layer environments. This paper identifies a fundamental trust gap between off-chain observations and on-chain consensus. We adapt OCR-style off-chain aggregation to Symbiotic Blockchain Networks (SBNs) and analyze its role as a pre-consensus validation layer for noisy and adversarial wireless service observations. The contributions are threefold: (i) formulation of trust in symbiotic 6G systems as a decentralized aggregation problem under uncertain PHY observations; (ii) design of a selective anchoring mechanism that records only quorum-approved outcomes; and (iii) analytical and experimental evaluation indicating improved trust robustness while preserving scalability, latency, and energy efficiency. Our proposed approach provides a practical foundation for trustworthy symbiotic service exchange in large-scale 6G environments.
Experimental results on a hardware prototype demonstrate that compared with no-blockchain trust-by-default baselines, the zero-trust overhead of TrustAgentNet is dominated by off-chain inference, while the blockchain layer incurs minor ledger costs via the ledger-IPFS storage and on/off-chain integration design.
Yayu Gao, Yong Xiao, Hao Hu et al.· IEEE Transactions on Cogniti...· 0 citations
Elastic Proof-of-Location Byzantine Fault Tolerance is proposed, a privacy-preserving and location-aware blockchain consensus framework for IoT systems that reduces communication overhead and improves consensus efficiency compared with conventional PBFT-based approaches while strengthening resilience against location-based and identity-based attacks.
Yunus Kareem, D. Djenouri, Essam Ghadafi· Future Internet· 0 citations
BEAT (Blockchain–Edge AI Trust) is presented, which closes that gap through co-design of three coupled layers: a Graph Attention Network–Long Short-Term Memory (GAT-LSTM) edge module that converts device interaction graphs into normalised trust evidence vectors.
Pavansai Ramarao Maddali, Vijay Kumar Damera, Ratna Kumar Prathipati· International Journal of Adv...· 0 citations
Simulation results show that compared with standard PBFT, Q-PBFT, and APBFT, H-PBFT exhibits significant advantages in consensus latency, throughput, and view switching recovery time, and maintains high system robustness even in complex network environments with malicious nodes.
Zhenhua Wang, Jiangang Hu, Xinmeng Wang et al.· Future Internet· 0 citations
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.
M. A. Al-Khasawneh, D. Alsekait, K. Alkayid et al.· Scientific Reports· 0 citations
\RC, a participant trust framework that uses blockchain as an evidence and provenance layer rather than as the source of trust, and supports a bounded reduction in reputation distortion, not attacker detection.
Adnan Iftekhar, Chengliang Zheng, Xiaohui Cui et al.· 0 citations