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.
Abstract
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.
Smart cities increasingly depend on large-scale Internet of Things (IoT) infrastructures for traffic management, smart grids, and environmental monitoring. Ensuring data integrity, transparency, and privacy in such systems remains a major challenge because centralized platforms are vulnerable to manipulation, while conventional blockchain-based solutions suffer from scalability and confidentiality limitations. This study proposes TrustIoT-Chain, a privacy-preserving blockchain framework that integrates off-chain digital twins, cryptographic data commitments, zero-knowledge compliance verification, and a sharded blockchain architecture for scalable smart city monitoring. The objective of this work is to provide real-time verifiable IoT monitoring with strong privacy guarantees and high system throughput. Large-scale simulations with one million synthetic IoT events demonstrate that the proposed framework achieves up to 24,910 events/s throughput with an average verification latency of 410 ms using 16 shards. Energy consumption is reduced by approximately 45% compared with non-sharded blockchain systems with zeroknowledge proofs, while privacy leakage measured by mutual information decreases to 0.05 bits. The key novelty lies in the joint integration of the digital twins with the blockchain-based zero-knowledge auditing, and sharding for the smart city IoT systems. This approach enables transparent regulatory compliance verification without exposing the raw sensor data, offering the scalable, and privacy-aware foundation for the future smart city governance, and trusted IoT ecosystems.
Shrutika Khobragade, J. Bakal· 2026 7th International Confe...· 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
Security in resource-constrained IoT deployments remains a persistent challenge: devices used in industrial control, smart healthcare, and transportation must authenticate quickly, consume minimal energy, and resist physical attacks — yet existing protocols rarely address all three requirements at once. To the best of current knowledge, no prior protocol jointly optimises security, energy, and latency within a single formally verified framework. This paper presents OPAQUE-IoT, an Optimization-driven PUF-Blockchain AKA Protocol for constrained IoT networks. The framework integrates PUF-based hardware identity verification, a permissioned blockchain for decentralized trust management, and the Adaptive Security-Energy Trade-off Optimizer (ASETO), which jointly minimizes authentication latency and energy consumption under formal security constraints. Convergence of ASETO is proven under Lipschitz-continuous objective functions. Formal security analysis under the Real-or-Random (RoR) model with explicit Random Oracle and ECDH hardness assumptions demonstrates resistance to replay, impersonation, man-in-the-middle, PUF modeling, insider, and side-channel attacks, with a security advantage bound of approximately 2^(-68). Simulation results across heterogeneous IoT topologies (N = 50 to 5000 devices) show 31.8% lower energy consumption, 30.2% reduced authentication latency, and 41.1% higher throughput compared to the best-performing blockchain-capable baseline, with O(log N) Merkle-indexed blockchain query complexity and O(T_max·N·P) per-epoch optimiser complexity.
Ibrahim Aqeel· Journal of King Saud Univers...· 0 citations
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 is proposed.
K. Venkatesh, Gorre Bharath, Jannu Subhas Chandra Boss· International Scientific Jou...· 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 introduction of blockchain technology has revolutionized decentralized systems. Blockchain enables peer-to-peer (P2P) transactions to be trustworthy and transparent. However, existing traditional consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS) have significant issues regarding computational costs, efficiency, and centralization, which severely limit their adoption in resource-constrained environments. For instance, in an industrial Internet of Things (IoT) network or a smart metering infrastructure, devices operate on strict energy budgets and cannot participate in compute-heavy PoW mining. They also lack the capital to lock up financial stakes for PoS. To address those limitations, randomized consensus mechanisms such as Pure Proof of Stake (PPoS) and Proof of Luck (PoL) were introduced. Yet these methods have issues with fairness, secure randomness generation, and cost efficiency. This paper proposes a new randomized proposer selection mechanism for blockchain consensus called Proof of Proximity (PoP) that enhances unpredictability, fairness, decentralization, and security. PoP replaces cryptographic randomness beacons with transaction-derived entropy and distance minimization. This enables fair, unpredictable proposer selection without relying on Verifiable Random Functions (VRFs), trusted hardware, or stakebased weighting, maintaining low computational overhead. The mechanism is ideal for IoT networks where resource consumption and security are critical. Experimental and comparative analysis results prove that PoP achieves improved fairness, decentralization, security, and low resource consumption, making it suitable for resource-constrained decentralized systems.
Nelum Ranawaka, L.A.M.S. Gawesh, G.O. Sundarasekara et al.· Annual International Compute...· 0 citations