Search Results (256)

Ensuring data security and privacy has emerged as a serious concern in the realm of blood supply chain. This is mainly because of sensitivity of donor information, the involvement of multiple stakeholders, and the need for transparent traceability. This paper proposes a novel privacy-preserving, permissioned blockchain framework for blood supply chain management that integrates Hyperledger Fabric, the InterPlanetary File System (IPFS), and a Zero-Knowledge Proof (ZKP)-based authentication protocol. The framework introduces a Pseudonymous Role-Bound Zero-Knowledge Authentication (PRZKA) mechanism that enables donors to authenticate and authorize access to their medical data without revealing their real identities. Context-specific pseudonyms derived through cryptographic hash-to-curve operations ensure unlinkability across different healthcare interactions, while Schnorr-style challenge–response proofs prevent replay attacks and credential misuse. Sensitive donor information is protected using Fabric Private Data Collections, whereas encrypted medical records are stored off-chain in IPFS, with only secure content identifiers recorded on the blockchain. Smart contracts enforce fine-grained, consent-aware access control policies and maintain immutable audit logs of all access events. The proposed system architecture combines an off-chain ZKP gateway with on-chain authorization logic to minimize blockchain overhead while preserving strong security guarantees. Furthermore, a performance evaluation framework is defined, including metrics, workload scenarios, and system configurations, to support future empirical validation. Security analysis indicates that the proposed framework enhances privacy, prevents identity linkage, and enables auditable, consent-driven data sharing compared with existing blockchain-based healthcare solutions. Full article

The proliferation of Internet of Things (IoT) devices has created unprecedented challenges in cybersecurity, as billions of interconnected devices generate, process, and transmit sensitive data across diverse networks. This study addresses critical security vulnerabilities in IoT ecosystems, focusing on the development of a comprehensive security framework that encompasses device authentication, an attribute access control mechanism, and privacy preservation. This work introduces HADA, a proposed hybrid authentication method that combines the validation of unique credentials and trust value. For the authentication of the data owner and user, the following credentials are validated: identity, certificate, reconfigurable physical unclonable function (PUF), and trust. Differential privacy is used to secure the credentials during information exchange. Then, the newly developed dynamic attribute access control method selects the number of attributes and matches the attributes; these two processes are performed using the Bi-Fuzzy logic and graph neural network (GNN) algorithms, respectively. After matching the data, the user is allowed to access them from the cloud server. For data encryption, the lightweight SKINNY algorithm is implemented in Hyperledger Fabric blockchain. The proposed system performs better than existing methods in terms of throughput, latency, and resource utilization. Full article

Modular integrated construction (MiC) is an innovative construction method that shifts on-site activities to a controlled factory environment, thereby offering sustainability benefits. However, current carbon management relies on labor-intensive manual data collection, causing delayed and inaccurate carbon accounting that increases greenwashing risks. Existing approaches lack real-time, automated, and trustworthy carbon tracking capabilities across fragmented supply chains. This study develops and validates the Blockchain-enabled IoT-BIM Platform (BIBP), which combines Internet of Things (IoT), Building Information Modeling (BIM), and blockchain for real-time carbon monitoring. IoT sensors automate data capture from construction equipment and BIM provides spatial visualization of carbon at the module and building levels. A Hyperledger Fabric blockchain ensures the authenticity, immutability, and traceability of carbon records. Validated on a 15-story MiC project in Hong Kong, BIBP established a cradle-to-end-of-construction baseline of 949.84 kgCO_2e/m², identifying steel and concrete as the primary hotspots (80% of material emissions). Real-time analytics demonstrated that combining high-volume ground granulated blast furnace slag (GGBS) concrete substitution, new energy sea–land multimodal transport, and 10% steel waste reduction achieves over 20% carbon savings. Furthermore, the BIBP automated data acquisition and calculation, improving assessment efficiency by 92.4%. The platform demonstrates the potential to transform carbon management from a static, retrospective evaluation into a proactive, data-driven monitoring process, equipping stakeholders with a tool to dynamically track emissions and make timely interventions toward carbon reduction targets. Full article

The secure management of classified documents containing sensitive information is critical for governments, military organizations, and the industry. Traditional data loss prevention (DLP) systems lack robustness against insider threats, particularly regarding access log integrity and tamper-proof auditing. To address log security, the previous literature has proposed multiple solutions, including private and hybrid blockchain models (e.g., Ethereum + MultiChain) to ensure audit trail integrity. However, hybrid architectures often face challenges such as unpredictable transaction costs (gas fees) and potential privacy risks when scaled for enterprise DLP logs. Conversely, private architectures may require higher resources, potentially causing bottlenecks on endpoints. In this paper, we propose an optimized Blockchain-Based Classified Document Management System (B2CDMS) utilizing a permissioned architecture. Our work demonstrates the challenges, advantages, and weak points of current solutions. We optimized a permissioned blockchain (BC) (Hyperledger Fabric v2.5) with an External Chaincode Builder using the Chaincode-as-a-Service (CCaaS) pattern. We compared our proposed private architecture with a hybrid architecture (Ethereum + MultiChain) and a public solution (Ethereum). We conducted a comprehensive analysis using pseudo Trellix ePolicy Orchestrator (ePO) Data Loss Prevention (DLP) logs. Experimental results on an Apple Silicon M4 (Apple Inc., Cupertino, CA, USA) testbed show that the proposed architecture achieves a throughput of 845.8 Transactions Per Second (TPS) with a sub-second latency of 55 ms, aiming to eliminate the bottlenecks of public blockchains. Furthermore, the system introduces a privacy-preserving hashing mechanism (i.e., committing only deterministic Secure Hash Algorithm 256-bit (SHA-256) digests to the immutable ledger while keeping the actual sensitive Personally Identifiable Information (PII) strictly in off-chain databases) compliant with General Data Protection Regulation (GDPR). It ensures that classified document metadata remains immutable and secure against rogue access benefiting from admin privileges. This study concludes that permissioned blockchain architectures offer a scalable and resource-efficient solution for forensic evidence preservation throughout the classified document lifecycle. Full article

In this paper, we present a system built on Hyperledger Fabric (HLF) that leverages Confidential Computing (CC) technologies to strengthen data privacy guarantees beyond those achievable through application-level mechanisms alone. While HLF natively supports data confidentiality through Private Collections (PCs), which restrict data visibility to a subset of authorized network participants, these mechanisms do not protect data at the hardware level: a privileged or compromised hosting platform can access plaintext data in memory and on the filesystem irrespective of HLF access control policies. To address this limitation, we integrate CC into HLF by adopting Intel Software Guard Extensions (SGX) in conjunction with the Gramine framework. This integration enables the execution of HLF components—peer nodes, orderers, Chaincodes and client applications—within Trusted Execution Environments (TEEs). Furthermore, to securely grant access to selected data to a trusted third-party software (TPS) external to the blockchain network, we leverage the Remote Attestation (RA) feature provided by CC, as streamlined by Gramine and enforced on a per-request basis, ensuring that only verified enclaves (or “SGX enclaves”) with expected measurements may access private data. In addition, the Sealing mechanism is employed to persistently store cryptographic material required by HLF components on the filesystem while preserving both confidentiality and integrity. Together, PCs, RA, Sealing, and enclave-based execution establish a layered privacy guarantee: PCs enforce application-level data segregation among channel participants; RA provides measurement-based access control for an external TPS; Sealing ensures that cryptographic material and blockchain state remain encrypted on the filesystem; and enclave-based execution protects data in use through hardware-level memory encryption. The proposed system has been applied and experimentally validated in a logistics use case in the Port of Genoa: benchmarks against an experimental HLF deployment demonstrate an average 95th-percentile (p95) performance overhead of approximately 1.3× attributable to SGX memory encryption and Gramine-based enclave execution, whereas an elevated memory usage footprint (33–35 GB per organization) has been measured, mainly due to the Gramine environment: this remains an open direction for future work. Full article

Infectious disease outbreaks continue to pose a significant threat to global health, underscoring the importance of timely detection and reliable reporting for effective interventions. Traditional reporting systems often rely on hierarchical data flows, which introduce delays, inconsistencies, and vulnerabilities, as highlighted during the COVID-19 pandemic. Blockchain, a disruptive technology, offers a promising solution. This study proposes a blockchain-based infectious disease reporting system built on Hyperledger Fabric that supports multi-level reporting and governance across national health systems. The architecture preserves hierarchical structures while enabling real-time reporting across authorized health stakeholders. It separates public test results from sensitive patient information, with private data secured via Private Data Collections and anchored using cryptographic hashes. Smart contracts enforce role-based access and validation, ensuring data integrity and controlled oversight. The system prototype was deployed within Docker containers and evaluated using illustrative COVID-19 case data. Network performance was benchmarked using Hyperledger Caliper, measuring throughput, latency, and resource utilization. The results demonstrate proper system functioning and stable transaction processing under the tested experimental conditions, supporting the feasibility of the proposed architecture for privacy-preserving multi-level infectious disease reporting systems. Full article

Current peer-to-peer (P2P) energy trading systems face important challenges in decentralised trading environments, particularly in managing participant trustworthiness, preventing dishonest behaviour, and mitigating transaction defaults. These limitations reduce transaction reliability and weaken trust among participants in community-scale energy trading markets. Although P2P energy trading enables communities to exchange locally generated renewable energy in smart environments, existing platforms often lack effective mechanisms to regulate participant behaviour and support reliable transactions. This paper proposes RepuTrade, a blockchain-based P2P energy trading platform tailored for community-scale microgrids. The proposed framework integrates a reputation-based consensus mechanism and a dynamic collateral management scheme that is directly linked to participant reputations such that trading reliability can be strengthened through behavioural incentives. In addition, a reputation-driven matching algorithm preferentially pairs highly reputable participants to improve market stability and trust. Simulation-based evaluation, involving 200 users across 8 trading rounds, shows that the RepuTrade framework consistently achieves higher trade success rates (92–99% compared to 83–95% in the baseline) and reduces defaults by more than 40% (27–44 vs. 55–72 per run). The results further reveal a strong negative correlation between user reputation and default probability, indicating that higher reputation is associated with a lower likelihood of dishonest behaviour. Overall, under the simulated settings considered in this study, the proposed framework improves transaction reliability and execution efficiency by reducing failed trades and lowering consensus validation latency. These findings contribute to the design of trust-aware decentralised energy trading mechanisms and provide simulation-based insights for developing more reliable and transparent community-scale renewable energy markets. Full article

Background: Blockchain and Multi-Agent System (MAS) are increasingly combined to support decentralized, secure, and autonomous peer-to-peer energy trading in microgrid environments. Objectives: This systematic review investigates how blockchain and MAS are integrated to support microgrid energy trading, identifies architectural and operational models, examines real-world implementations, and highlights technical, regulatory, and security challenges. Unlike prior reviews that focus on blockchain or MAS in isolation, this study provides a unified and comparative analysis of their joint integration. Methods: Following PRISMA 2020 guidelines, a systematic search was conducted in IEEE Xplore, ACM Digital Library, and ScienceDirect, with the last search performed on 10 January 2025. Eligible studies focused on blockchain–MAS integration in microgrid energy trading; non-energy and non-microgrid applications were excluded. Study selection was performed independently by two reviewers, and methodological quality was assessed using an adapted Joanna Briggs Institute (JBI) checklist. A narrative synthesis categorized integration levels, blockchain platforms, MAS roles, and implementation contexts. Results: A total of 104 studies were included. Three dominant integration levels were identified—basic, intermediate, and advanced—distinguished by how decision-making responsibilities are distributed between MAS and smart contracts. Ethereum and Hyperledger Fabric were the most commonly used platforms. MAS agents perform concrete operational functions such as bid and offer generation, price negotiation, matching, and local energy optimization, fundamentally transforming control and monitoring processes. By enabling distributed, intelligent agents to perform real-time sensing, analysis, and response, an MAS enhances system resilience and adaptability. This architecture allows for proactive fault detection, dynamic resource allocation, and coherent, large-scale operations without centralized bottlenecks. Blockchain ensured transparency, trust, and secure transaction execution. Major challenges include scalability constraints, interoperability limitations with legacy grids, regulatory uncertainty, and real-time performance issues. Limitations: Most included studies were simulation-based, with limited real-world deployment and substantial heterogeneity in evaluation metrics. Conclusions: Blockchain–MAS integration shows strong potential for secure, transparent, and decentralized microgrid energy trading. Addressing scalability, regulatory frameworks, and interoperability is essential for large-scale adoption. Future research should emphasize real-world validation, standardized integration architectures, and AI-enabled MAS optimization. Funding: No external funding. Registration: This systematic review was not registered. Full article

We explore the problems encountered by today’s enterprises when using traditional human resource management systems and task tracking management systems to propose the use of blockchain technology as an innovative solution for internal human resource management and task tracking management. To ensure the security, transparency, non-repudiation, and traceability of the information submitted by various parties in the entire life cycle of task tracking management, we propose a task tracking management system based on blockchain technology. The system architecture integrates the key stakeholders in the entire value chain of task tracking management in human resource management, including internal employees, department managers, and human resource management departments. The architecture integrates the internal work tracking and management process of the enterprise through blockchain technology, ensuring data non-repudiation through digital signatures. Asymmetric encryption and decryption technology are employed to prevent data leakage and resist ransomware attacks. Based on the above features, it is highly suitable for enterprise introduction and use. Full article

Peer-to-peer (P2P) energy-trading has emerged as a promising mechanism for decentralized electricity markets, but its practical deployment is often limited by the difficulty of accounting for physical network constraints and transmission losses in real time. This paper presents a decentralized P2P energy trading mechanism that incorporates network constraints and transmission losses directly into the market-clearing process. The framework combines Power Transfer Distribution Factors (PTDFs) for pre-trade feasibility validation with an Enhanced Least Squares Method (ELSM) for loss estimation, enabling loss-aware settlement without computationally intensive and redundant AC power flow calculations. The mechanism is implemented on Hyperledger Fabric using Attribute-Based Access Control, Access Control Lists and Private Data Collections to ensure privacy and auditability. Numerical studies on a 3-bus and the IEEE 39-bus system show that the proposed approach closely reproduces AC Optimal Power Flow dispatch and cost outcomes, while significantly improving simplified DC-based loss models. The results demonstrate that physically feasible and economically efficient decentralized trading can be achieved in a permissioned blockchain environment. Full article

Effective supply chain traceability is indispensable for ensuring food safety, which is a significant social issue. Traditional traceability systems are mostly based on centralized databases, relying on a single entity or organization and facing problems such as insufficient transparency and the risk of data tampering. To address these issues, many studies have adopted blockchain technology, which offers advantages such as decentralization and immutability. However, challenges such as data credibility and insufficient protection of private data remain. This study proposes a multi-channel architecture based on Blockchain (Hyperledger Fabric in this study), in which data is partitioned and managed across dedicated channels to strengthen the protection of sensitive information. Furthermore, a trust and incentive design is implemented, featuring a trust-value calculation function and a reward–penalty mechanism that encourage participants to upload more truthful data and improve the reliability of data before it is recorded on the blockchain. In this paper, the design and implementation of the proposed system are explained in detail, and its performance is examined using Hyperledger Caliper, a blockchain performance benchmark framework. Functional evaluations indicate that the proposed system can be correctly implemented and that it correctly supports supply chain traceability, trust- and incentive-related, privacy protecting and other functions as designed, while performance evaluations indicate that it can maintain stable performance under higher workloads, suggesting that the proposed approach is practical and applicable to food supply chain traceability scenarios. Full article

Ensuring the reliable, auditable, and privacy-oriented distribution of donations in disaster logistics constitutes a critical challenge due to multi-stakeholder coordination difficulties and the risk of misuse. This study presents a modular architecture, named SecureRelief, operating on a permissioned Hyperledger Fabric platform. The architecture integrates authentication based on Self-Sovereign Identity (SSI), Decentralized Identifiers (DID), and WebAuthn, together with Attribute-Based Access Control (ABAC), and enables the verification of delivery evidence through privacy-preserving validation using zero-knowledge proofs (ZKP). Documents are stored off-chain on the InterPlanetary File System (IPFS), while only cryptographic summary (hash) values sufficient for integrity verification are maintained on-chain. In scenario-based laboratory experiments, the blockchain layer demonstrated low latency (p95 < 16 ms) and stable transaction throughput, confirming its scalability. While the API layer handled high burst request loads with a 0% error rate, the additional computational overhead introduced by the integrated privacy-preserving (ZKP) mechanisms kept the end-to-end transaction latency within acceptable limits for disaster management applications (3.5–4.5 s). Full article

With the rapid development of online aquatic product trading, traditional centralized platforms are facing increasing pressure in terms of data security, privacy protection, and trust. Problems such as tampering with transaction records, weak identity authentication, privacy leakage, and the difficulty of balancing matching efficiency with security limit the further development of these platforms. To address these issues, this paper proposes a blockchain-based identity authentication and access control scheme for online aquatic product trading. The scheme first introduces a dual authentication mechanism that combines a verifiable random function with a Schnorr-based zero-knowledge proof, providing strong decentralized identity verification and resistance to replay attacks. It then designs a dynamic access control strategy based on a multi-dimensional reputation model, which converts user behavior, attributes, and historical transaction performance into a comprehensive trust score used to determine fine-grained access rights. In addition, an AES-PEKS hybrid encryption method is employed to support encrypted keyword search and order matching while protecting the confidentiality of order data. This paper implements a multi-channel architecture for aquatic product trading prototype system on Hyperledger Fabric. This system separates registration, order processing, and reputation management into different channels to improve concurrency and enhance privacy protection. Security analysis shows that the proposed solution effectively defends against replay attacks, key leaks, data tampering, and privacy theft. Performance evaluation further demonstrates that, compared to a single-chain architecture, the multi-channel design, while increasing security mechanisms, maintains a stable throughput of approximately 223 tx/s even when concurrency reaches 600–800 tx/s, ensuring normal operation of the trading system. These results indicate that this solution provides a practical technical approach and system-level reference for building secure, reliable, and efficient online aquatic product trading platforms. Full article

Secure and auditable data sharing in large-scale Internet of Things (IoT) environments remains a significant challenge due to weak trust coordination, limited scalability, and susceptibility to emerging quantum attacks. This study introduces a hybrid blockchain-based framework that integrates post-quantum cryptography with intelligent anomaly detection to ensure end-to-end data integrity and resilience. The proposed system utilizes Hyperledger Fabric for permissioned device lifecycle management and Ethereum for public auditability of encrypted telemetry, thereby providing both private control and transparent verification. Device identities are established using quantum-entropy-seeded credentials and safeguarded with lattice-based encryption to withstand quantum adversaries. A convolutional long short-term memory (CNN–LSTM) model continuously monitors device behavior, facilitating real-time trust scoring and autonomous revocation via smart contract triggers. Experimental results demonstrate 97.4% anomaly detection accuracy and a 0.968 F1-score, supporting up to 1000 transactions per second with cross-chain latency below 6 s. These findings indicate that the proposed architecture delivers scalable, quantum-resilient, and computationally efficient data sharing suitable for mission-critical IoT deployments. Full article

The rising usage of IoT devices in everyday life has formed smart cities that require the adoption of decentralized systems for a secure and transparent mechanism to manage asset exchange across automotive supply chains. Several existing Blockchain-based models built on public chains focus on traceability while overlooking scalability limits, transaction fees, conditional payment trust, or real-time delivery validation. We introduce DeFiTrustChain, a DeFi-enabled framework that combines free NFTs, escrow-based automation, and IoT verification within a Hyperledger Fabric network. It represents each vehicle using a unique NFT to capture the details of manufacturing and ownership, along with immutable asset verification. The payment release between stakeholders is governed by a dedicated escrow contract responsible for IoT-based delivery confirmation. The proposed framework ensures authenticated access and prevents identity misuse through integration of the Fabric Certificate Authority. The experimental results demonstrate the coherent and dependable execution of NFT creation, escrow enforcement, and IoT-triggered validation, with low local transaction processing time and consistent behavior across peers. Full article