Jul 2026· 2026 7th International Conference on Smart Systems and Inventive Technology (ICSSIT)· pp. 617-626· 0 citations· 24 references
Abstract
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.
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
The growing nature of global supply chains has posed a great challenge in terms of providing a level of transparency, security, scalability, and privacy among the distributed logistics networks. Conventional supply chain management systems are based on the central databases that are susceptible to alteration of data, fraud and insufficient interoperability between the stakeholders. Despite the fact that blockchain technology has became a promising solution to enhance supply chain transparency and traceability, scalability, the high transaction latency, privacy leakage, and energy-consuming consensus mechanisms are current limitations with regard to the existing blockchain-based systems. This paper has provided a new framework to solve these problems which includes AI-driven Adaptive Sharded Blockchain with Zero-Knowledge Traceability (AASB-ZKT) of smart supply chain. The solution proposed combines the use of artificial intelligence-based anomalies detection, dynamically sharded blockchain, privacy protection based on zero-knowledge proofs, smart contracts powered by IoT, and opinion-based weighted consensus. The framework is meant to enhance the throughput of transactions, decrease the latency, increase fraud detection, and provide privacy without traceability. The empirical analysis conducted on the experimental basis proves that the suggested strategy is much more effective in enhancing the scalability, security, and operational efficiency in contemporary supply chain environments.
R. Sreekumar, M. Nidhi· International Conference on...· 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
Ensuring transparency, security, and privacy in agricultural food supply chains is critical for maintaining consumer trust, regulatory compliance, and data integrity. Traditional centralized traceability systems suffer from several limitations, including data tampering risks, single-point failures, and potential privacy leakage. To address these challenges, this research proposes a privacy-preserving blockchain-based traceability framework that integrates the InterPlanetary File System (IPFS) with Zero-Knowledge Proofs (ZKPs). The framework leverages the Ethereum blockchain for immutable record-keeping, while zk-SNARK-based proofs enable compliance verification without revealing sensitive underlying data. A prototype was implemented using Solidity smart contracts and Python-based zk-SNARK circuits. Experimental evaluation across varying record sizes, from 50 to 200, demonstrates high security and efficiency, achieving 100% success in detecting simulated tampering attempts. Performance metrics indicate a highly scalable system with an average end-to-end latency of approximately 0.33 seconds, rapid proof generation times of approximately 0.0002 seconds, and near-constant verification times averaging 0.027 seconds. Furthermore, the system maintains a consistent simulated transaction cost of 20.40$ per proof, regardless of the total records processed. Overall, the proposed approach provides a robust, scalable, and computationally efficient solution for modern agri- food supply chains, successfully balancing data confidentiality with rigorous cryptographic integrity.
Priya Patel, Nitesh M. Sureja· International Research Journ...· 0 citations
The proposed BlockSafeNet framework achieved significant improvements in secure IoT communication, privacy preservation, and AI-driven cyber threat detection within smart city infrastructures, providing a positive impact on the SC ecosystem.
Kanika Duggal, Gi-Chon Park· Telecom· 0 citations
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