Aug 2026· Journal of Intelligent Decision Making and Information Science· 0 citations· 29 references
TL;DR
HBTV-SR, a permissioned blockchain-assisted trust-evidence retrieval method for secure IoT/WSN routing, indicates that edge-assisted ledger-backed trust retrieval improves secure routing reliability while avoiding excessive blockchain workload on constrained IoT/WSN nodes.
Abstract
Secure routing is a critical requirement for Internet of Things (IoT) and wireless sensor networks (WSNs) that form the sensing layer of future internet and edge-assisted communication systems. Shortest-path routing alone cannot provide reliable delivery when intermediate nodes exhibit selective forwarding, malicious dropping, or inconsistent behavior. This paper presents HBTV-SR, a permissioned blockchain-assisted trust-evidence retrieval method for secure IoT/WSN routing. The proposed design keeps ordinary sensor nodes lightweight by allowing them to generate signed trust observations, while miner/gateway edge nodes verify signatures, freshness, the absence of duplicate hashes, evidence completeness, and trust-value ranges. Storage nodes maintain Merkle-rooted trust records for tamper-evident retrieval. A reproducible packet-level simulator evaluates HBTV-SR against AODV-like routing, TARF-style trust routing, a direct She et al. blockchain trust baseline, and other baselines surveyed in the literature for the same scenario. Across 30 fixed-seed Monte Carlo runs, HBTV-SR achieved 83.12% packet delivery ratio in the representative 100-node, 20% malicious-node scenario, compared with 78.21% for the She et al. baseline. The results indicate that edge-assisted ledger-backed trust retrieval improves secure routing reliability while avoiding excessive blockchain workload on constrained IoT/WSN nodes.
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
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
Wireless Sensor Networks (WSN) are significant for various applications, however ensuring data security and energy consumption remains a critical challenge. The conventional methods lacked sufficient security, exhibited communication overhead, and energy inefficiencies. Therefore, this research proposes the Distributed Fractional Hawk Optimization (DtFHO) algorithm to address the limitations in cluster head selection for secure WSN routing. The integration of fractional theory improves the convergence speed and exploitation balance in cluster head selection. To secure the data routing, a blockchain network is employed, which maintains a transparent record of routing paths while preventing malicious node entries. Furthermore, the modified End-to-End Homomorphic encryption enables secure data sharing without decrypting sensitive information at intermediate nodes. Through considering the multimetric factors, the DtFHO algorithm offers a secure routing path, making it highly effective for large-scale and sensitive network scenarios. The DtFHO showcases a robust performance by achieving a minimum transaction time of 2.013 seconds, memory usage of 347.95 Kilobytes, Gas usage of 345.84 Kilobytes, encryption time of 2.012 seconds, and a maximum throughput ratio of 0.748, normalized energy of 0.766 Joules, with 153 alive nodes compared to the conventional methods.
Manish Agarwal, Aasheesh Shukla, V. Deolia· 2026 4th International Confe...· 0 citations
The use of a wireless sensor network is increasingly supporting e-governance functions such as municipal utility monitoring, environmental monitoring, grievance-based field reporting, and smart public service delivery. Most wireless sensor network architectures rely on a gateway or database. However, this introduces vulnerabilities to data integrity, node accountability, and auditability. This study examines transparency through a blockchain-enabled WSN architecture for e-governance. The study applies a reproducible Python-based Monte Carlo simulation with a fixed random seed, five node densities, three architectural scenarios, and 450 observations. The scenarios that are compared in this work are a normal WSN, a centralized secure WSN, and a permissioned blockchain-enabled WSN with smart-contract-based identity registration, hash-linked data records, trust scoring, and tamper verification. Descriptive statistics, one-way ANOVA, Welch t-tests, Pearson correlation, and multiple linear regression analysis. The blockchain-assisted WSN, as evidenced by the simulation findings of our project, produced the highest mean data integrity score, tampering detection rate, trust score, malicious node detection rate, and packet delivery ratio. The architecture also improved the composite service efficiency index relative to the conventional baseline, even though it introduced higher latency, transaction confirmation time, and energy consumption. The research indicates that the permissioned blockchain can enhance public-sector WSN transparency with edge aggregation and lightweight cryptographic operations along with carefully tuned endorsement rules. The methods presented in this study allow for scrutiny of secure WSN designs tailored for e-governance.
Vivek Kumar and Sumit Lal· International Journal of Adv...· 0 citations
With the rapid increase of Internet of Things (IoT) devices, it is a challenge to ensure secure and reliable device authentication. Conventional blockchain-based solutions provide immutability and transparency, but dynamic trust management is not present, resulting in limited scalability in heterogeneous IoT environments. To overcome these drawbacks, this study presents a blockchain-integrated trust-based authentication and access control framework designed specifically for IoT networks. The proposed model combines deterministic blockchain validation with probabilistic trust computation, enabling adaptive decision-making while preserving system integrity. Performance analysis highlights the efficiency of the approach: decryption consistently executes in less than one second, trust score evaluation completes within two seconds, and memory usage demonstrates storage efficiency. During trust updates, memory requirements peak at 173.1 MB, while image processing operations consume slightly more memory. Incremental growth during trust point updates is minimal, around 2.9 MB, indicating lightweight overhead. The results confirm that the architecture achieves a strong balance between security and performance, offering rapid authentication without compromising resource efficiency. By merging blockchain policy enforcement with trust reasoning, the framework advances current IoT security mechanisms and offers a scalable solution applicable across domains such as smart homes, industrial automation, and edge computing.
S. Deepthi, Khoi A. Tran, G. Deepa· SN Computer Science· 0 citations
Cognitive Radio Networks (CRNs) are a new era of wireless communication systems that enable secondary users to access spectrum bands opportunistically when primary users are not using them. Although a CRN can provide high-quality service and enhance spectrum utilization, there are still some important urgent problems to be solved, such as insecure communication, malicious nodes participating in the network, and unreliable routing performance. However, none of the existing security and communication schemes can achieve trusted entity validation, shortest-path optimization, and communication reliability simultaneously in CRNs. To address these challenges, this paper presents the AI assisted Blockchain Decentralized Zero Trust Authentication (BDZTA) approach for secure communication in CRN. Initially, the proposed Trust-Energy Aware Transmission Node Assessment (TEATNA) method is employed to identify the reliable transmission nodes. Then, the Adaptive Graph Neural Network (AGNN) model is used to classify the optimal shortest communication path by capturing the dynamic topological structure among cognitive radio nodes. After optimal route selection, Quantum-Inspired Whale Optimization with Elliptic Curve Cryptography (QIWO-ECC) approach is utilised for key generation and lightweight data encryption. Subsequently, the BDZTA approach is used to enable secure, decentralized communication through continuous identity verification. Finally, the Proof of Authority Verification (PoAV) scheme is used to validate authorized communication entities and ensure secure participation in transactions. The integrated framework significantly improves secure communication, trusted routing, Packet Delivery Ratio (PDR), energy efficiency, end-to-end delay, and energy consumption. The results of the experimental analysis show that the proposed approach achieves the best performance among existing schemes, thereby providing strong, reliable, and intelligent communication in CRNs.
T. Sundar, A. Senthilkumar· International journal of com...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
