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.
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
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.
Priyanka Singh, Sonam Dubey· 2026 4th International Confe...· 0 citations
The rapid growth of Internet of Things (IoT) systems has introduced significant challenges related to privacy, trust, scalability, and attack resilience, particularly in resource-constrained and location-sensitive environments. Existing blockchain consensus mechanisms provide decentralised trust, but they often suffer from high communication overhead, weak physical-context awareness, and limited privacy protection when deployed in large-scale IoT networks. This paper proposes Elastic Proof-of-Location Byzantine Fault Tolerance (EPoLBFT), a privacy-preserving and location-aware blockchain consensus framework for IoT systems. The proposed design enables IoT nodes to prove regional eligibility without revealing exact coordinates while restricting consensus participation to trusted and geographically verified validators. EPoLBFT is evaluated using the Blockchain IoT Consensus Algorithm (BICA) simulator under normal, high-load, Byzantine, Sybil, location-spoofing, and denial-of-service scenarios. The evaluation considers latency, throughput, communication overhead, energy consumption, and attack resilience. The results show that EPoLBFT reduces communication overhead and improves consensus efficiency compared with conventional PBFT-based approaches while strengthening resilience against location-based and identity-based attacks. The study also discusses the privacy–latency trade-off introduced by zk-PoL, the assumptions related to trusted location anchors, and the limitations of simulation-based evaluation.
Yunus Kareem, D. Djenouri, Essam Ghadafi· Future Internet· 0 citations
Secure and transparent system for recording and verifying digital transactions across distributed networks. Distributed blockchain consensus is achieved through decentralized protocol rules, cryptographic authentication mechanisms, and scalable energy-efficient operations. The present study applies Quantum Mayfly Optimization (QMFO) within a blockchain-based collaborative intrusion detection framework. Collaborative intrusion detection systems (CIDS) have certainly carved their valued place in enhancing modern cybersecurity in the complex landscape of cyber threats. What the BCIDF brings into the picture is a new radical avenue to enhance the detection of new threats and information sharing. In this respect, the proposal cohesively combines distributed blockchain technology and collaborative intrusion detection to increase security, transparency, and trust within cyber realms. Fine-tuning the model parameters will improve blockchain classification accuracy and efficiency, and O(QMFO), a bio-inspired hybrid algorithm inspired by the principles of quantum leaf-edge swarm behavior, is directed toward ensuring the security and performance of blockchain networks. Quantum Mayfly optimization (QMFO) and a Blockchain-based Collaborative Intrusion Detection Framework (BCIDF) are designed to secure distributed networks by allowing tamper-resistant sharing of alerts in the case of an attack across the blockchain. The term 'Quantum Mayfly Optimizer (QMFO)' here is used to amplify performance, speed, and accuracy. Integration, therefore, guarantees the best detection and few false positives, and ensures adaptive actions against upcoming threats.
M. Savitha, I. P. Stella Mary, A.Manikandan et al.· 2026 6th International Confe...· 0 citations
The exponential growth of cloud computing has enabled large-scale data outsourcing but has simultaneously introduced critical challenges related to data confidentiality, integrity, and trust. Traditional cryptographic and blockchain-based cloud security solutions often suffer from high computational overhead, latency, and scalability limitations, which hinder their practical adoption. To address these issues, this study proposes a robust and lightweight blockchain-based security framework for secure cloud data storage. The framework integrates hybrid AES–ECC encryption, smart contract–driven access control, and a lightweight consensus mechanism combining Delegated Proof of Stake (DPoS) and Practical Byzantine Fault Tolerance (PBFT) to achieve efficient and tamper-resistant data management. The proposed system employs an on-chain/off-chain hybrid architecture that stores only essential metadata and cryptographic proofs on the blockchain while maintaining the actual data in distributed cloud storage. This design minimizes computational burden and blockchain bloat while ensuring end-to-end transparency and verifiability. A Merkle tree–based Proof of Storage (PoS) mechanism enables rapid integrity verification without requiring full data retrieval. Comprehensive experiments were conducted using a simulated multi-node cloud environment to evaluate encryption efficiency, transaction latency, throughput, storage overhead, and energy consumption. Results show that the proposed framework outperforms existing blockchain-based models, achieving a 37.7% reduction in encryption/decryption time, a 51.3% decrease in transaction latency, and a 54.5% improvement in energy efficiency. Additionally, the system attained a 99.3% security success rate under various attack scenarios, demonstrating its resilience against unauthorized access, replay, and tampering attempts. These findings confirm that the proposed approach provides a practical balance between security assurance and performance optimization.
R. Bala, S. Gnanavel· International Journal of Adv...· 0 citations
ABSTRACT
The rapid growth of the Internet of Things (IoT) has enabled billions of interconnected devices to exchange data across smart cities, healthcare systems, industrial automation platforms, and intelligent transportation networks. Despite its transformative potential, IoT environments remain highly vulnerable to cyberattacks due to limited device resources, centralized architectures, weak authentication mechanisms, and insecure communication channels. Traditional security frameworks often struggle to provide scalable trust management and tamper-resistant data protection in large-scale IoT deployments. This paper proposes a Blockchain-Based IoT Security Architecture that integrates distributed ledger technology, smart contracts, edge computing, and zero-trust authentication mechanisms to enhance security, privacy, and system reliability. The proposed framework enables decentralized device authentication, immutable transaction recording, secure data sharing, and automated access control through blockchain networks. Smart contracts dynamically enforce security policies and verify device identities before granting network access. Experimental evaluation demonstrates improvements in attack resistance, data integrity, authentication efficiency, and network trustworthiness compared with conventional centralized security approaches. The proposed architecture provides a scalable and resilient security solution for next-generation IoT ecosystems.
Keywords: Blockchain, Internet of Things, Cybersecurity, Smart Contracts, Zero-Trust Architecture, Edge Computing, Distributed Ledger Technology, IoT Authentication.
K. Venkatesh, Gorre Bharath, Jannu Subhas Chandra Boss· International Scientific Jou...· 0 citations