Jul 2026· 2026 4th International Conference on Sustainable Computing and Smart Systems (ICSCSS)· pp. 1325-1330· 0 citations· 21 references
Abstract
New computing environments such as the cloud, edge, and Internet of Things (IoT) introduce new challenges in trust management, security, and energy efficiency. Centralized trust management systems focus on a single point of failure, making them less transparent and more vulnerable to attack. This paper presents the first trust framework based on blockchain technology to support security and sustainability in distributed computing systems. The methodology presented in this paper combines distributed ledger technology, smart contracts, and a lightweight consensus mechanism to provide a transparent and computationally inexpensive way to trust evaluation. To evaluate trust dynamically at a given node, a multi-factor trust model is used that incorporates trust, security, behavioral factors, and energy efficiency. A distributed system with 100 nodes and 1000 transactions per node was used to evaluate the framework experimentally. Results indicated that the proposed system attained a trust score of 95%, and performed better than centralized (82%) and reputation-based (88%) models. The system also improved energy efficiency by 26.7% relative to baseline systems, indicating that the computing system can be integrated to enhance sustainability. The blockchain framework trust models provided security and energy savings in distributed systems. It also presented robust designs and useful computational environments. Future extensions of this work will focus on Artificial Intelligence (AI) based trust prediction and on determining hybrid blockchains for performance improvements.
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
The growth of the Internet of Things (IoT) has introduced significant security challenges, mainly due to the resource constraints of devices and the limitations of centralized architectures. This paper proposes a blockchain-based Zero-Trust framework for secure and scalable IoT systems. The approach is architecture-agnostic and combines decentralized identity management, hybrid data storage, and edge-assisted computation. To optimize resource usage, raw data are stored off-chain while cryptographic hashes are anchored on the blockchain, ensuring integrity and immutability. A Merkle tree structure is employed to aggregate data efficiently, reducing communication overhead and blockchain transaction costs. Experimental results demonstrate that lightweight cryptographic mechanisms, combined with Merkle-based aggregation, provide strong security guarantees with low energy consumption. The proposed framework achieves improved scalability, robustness, and efficiency, making it suitable for resource-constrained IoT environments.
Florian Bonelli, Alexandre dos Santos Roque, E. P. de Freitas· International Conference on...· 0 citations
This work demonstrates that a dynamic, reputation-based security layer can provide near-total protection against the modeled threats at negligible performance cost, offering a viable, highly effective solution for securing resource-constrained IoT deployments.
N. N. A., A. T, Bhuvaneswari M.· Discover Internet of Things· 0 citations
The rapid proliferation of Internet of Things (IoT) devices under sixth-generation (6G) networks introduces a highly
dynamic, decentralized environment in which static, perimeter-based security models are no longer adequate. This paper
proposes AZTM-v3 an adaptive Zero Trust framework that couples behavior-driven trust management with a Random Forest
classifier to identify and isolate malicious nodes in real time. The framework is evaluated on an NS-3 simulation of a 150-node 6G
IoT network subjected to Sybil, Denial-of-Service (DoS), spoofing, replay and ON-OFF attacks. Unlike prior trust-management
proposals that report only qualitative or partial outcomes this work quantifies performance across five dimensions i.e detection
accuracy, F1-score, false-positive rate, end-to-end latency and consensus-convergence time and benchmarks AZTM-v3 against
PKI-based, centralized-trust and static-blockchain baselines. AZTM-v3 attains a 98.1% overall detection accuracy with a 1.6%
false-positive rate at 150 nodes and sustains 95.4% accuracy at 200 nodes outperforming the PKI baseline by 12–18 percentage
points across all tested loads. These results indicate that combining tiered trust evaluation with machine learning based
classification yields a measurably more scalable and resilient security layer for 6G-enabled IoT deployments than existing static
or purely cryptographic approaches.
Nelli Yaswanth Kumar, Singothu Jhansi Rani, Setti Sarika· International Journal for Re...· 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
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
