Search Results (1,520)

Blockchain architectures increasingly rely on smart contracts as programmable execution components, yet the security challenges they introduce remain only partially addressed. Fuzz testing has emerged as one of the leading automated techniques for smart contract vulnerability discovery; however, a systematic treatment linking classical fuzzing concepts to the specific architectural constraints of smart contract execution environments has remained elusive. We conduct a large-scale systematic review of 258 publications collected from Scopus and Google Scholar. The review is structured around four research questions covering general fuzzing limitations, EVM execution constraints, cross-contract interaction challenges, and technique transferability. The contributions are fourfold. First, we develop a conceptual taxonomy establishing an explicit correspondence between classical and smart contract fuzzing. Second, we present an architectural taxonomy of representative fuzzers unified under a generalised waypoint architecture that exposes key feedback domains and composition gaps. Third, we provide a categorised technique review spanning coverage-guided, hybrid, and learning-based approaches. Fourth, we offer a reproducibility critique with a structured research roadmap. Coverage-guided greybox fuzzing emerges as the dominant paradigm (51.2% of the 121 SC fuzzer tools); learning-based approaches (machine learning, reinforcement learning, and LLMs) are a small but emerging class, with LLM-guided fuzzing the fastest-emerging subcategory by recency. Feedback-domain composition remains sparse: most surveyed fuzzers combine only a few of the eight identified feedback domains, and none approaches the full set, leaving several high-value multi-domain compositions unexplored. Open challenges include scalable stateful exploration, standardised benchmarks and oracles, and EVM-specific architectural optimisations. The complete categorised corpus, coding, and search strategy are openly available. Full article

Operational redundancies in Nigeria’s airport logistics, including duplicated clearance procedures, fragmented data systems, and repeated physical inspections, generate substantial inefficiencies that hamper service delivery, increase costs, and raise sustainability concerns. Despite growing interest in blockchain technology (BCT) as a logistics innovation, empirical evidence from Sub-Saharan African aviation contexts is largely limited. This study examines how stakeholders perceive BCT as a potential mechanism for reducing procedural, informational, and structural redundancies across Nigerian airport operations. A qualitative research design was employed, drawing on 45 semi-structured interviews with airport managers, airline officials, regulatory bodies, and aviation experts. Data were analyzed using Leximancer, yielding eight thematic clusters across 115 concepts. To augment thematic rigor, three quantitative measures—Normalized Pointwise Mutual Information (NPMI), Jaccard similarity, and degree centrality—were applied to the exported Concept Co-occurrence Matrix (CCMatrix; 6555 pairwise relationships). The blockchain theme exhibited the highest intra-theme cohesion (mean NPMI = 0.615) and the second highest normalized centrality (0.638), suggesting that it functions as a semantically tight, cross-cutting concept in participants’ discourse. The strongest concept pair, inefficiency–reliability (NPMI = 0.989; Jaccard = 0.909), is consistent with participants’ recurring association of service failures with procedurally generated redundancies. Stakeholders perceived BCT as potentially addressing these redundancies through shared ledger architectures, smart contract automation, and consolidated identity management, with anticipated sustainability co-benefits across energy, documentation and processing domains. The study offers an exploratory, contextualized application of the Technology–Organization–Environment (TOE) framework, the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Dynamic Capabilities Framework (DCF) to a resource-constrained developing-country aviation context and proposes a stakeholder-informed, phased BCT adoption framework—not yet tested through implementation—with direct policy and managerial implications for the Nigerian airport administration. Full article

Poultry supply chains need to comply with Shariah requirements when supplying halal meat, which requires continuous quality improvement and multi-stakeholder inspection. However, current traceability systems have centralized opaque characteristics, fragmented records, and slow detection of anomalies, leading to food safety vulnerabilities and impractical recall protocols. To overcome these challenges, this paper presents an intelligent blockchain and Internet of Things (IoT)-based traceability system with a permissioned Hyperledger Fabric consortium network. A hybrid off-chain storage architecture supports scalable monitoring without ledger congestion: TimescaleDB stores high-frequency IoT sensor data (e.g., temperature and GPS), MinIO warehouses compliance documentation, while only immutable cryptographic hashes are stored on-chain to guarantee the integrity of the data. Halal governance is digitalized using role-based smart contracts that trigger real-time alerts, batch blocking, and automated recall upon environmental threshold breaches. Performance evaluation via Hyperledger Caliper indicates the system achieves 275 write transactions per second, a 300 TPS read throughput, an optimized read latency of 5 ms, and a write latency of less than 36 ms. Validated as a laboratory concept, this decentralized framework demonstrates proactive quality assurance, mitigates ledger bloat, and enhances halal-integrity trust. Full article

Artificial Intelligence and blockchain are converging in ways that are quietly reshaping how financial systems operate. AI brings predictive analytics, automated decision-making, and fraud detection; blockchain contributes an immutable, decentralised record that can be independently verified. Taken together, applications such as AI-augmented smart contracts and blockchain-anchored data pipelines are already changing how fraud is detected, how compliance is handled, and how decentralised finance (DeFi) functions. But the same combination that makes these systems powerful also makes them harder to govern: technical, regulatory, and ethical obstacles still stand in the way of adoption at scale. This paper uses a targeted, purposive literature synthesis alongside exploratory case analysis of financial institutions and fintech platforms to examine how AI and blockchain are transforming finance together, what barriers and systemic risks accompany that transformation, and where research and regulation need to go next. Drawing on the Technology Acceptance Model, Diffusion of Innovation Theory, and the Socio-Technical Systems perspective, the paper builds a multi-level framework for thinking about how AI–blockchain convergence can be adopted responsibly across the financial industry. Full article

Smart-city energy platforms—peer-to-peer markets and tokenized renewable energy certificates—settle against metered generation, yet never check the physical plausibility of those claims. For wind, attainable energy is not measured but derived from anemometry through a vertical extrapolation whose exponent—the wind-shear coefficient—is a discretionary modeling choice. Using a five-height, 52,192-record campaign from Phangan Island, Thailand—reproduced here as a statistically anchored reconstruction, the raw archive not being redistributable—we show that the conventional $1/7$ rule understates attainable energy by $29.8\%$, and that an adversary asserting the exponent could inflate a resource claim by $87.4\%$. WindChain sits beneath the smart-city transactive layer rather than beside it: it does not mint certificates from wind data but bounds what a revenue meter may claim. It enforces boundary-layer, kinematic, and thermodynamic admissibility as a consensus predicate and commits wind statistics to a hierarchical Merkle–Weibull accumulator whose 104-byte root lets any verifier recompute the Weibull parameters, power density, and shear exponent in constant time. We prove that an epoch-level admissibility gate bounds over-issuance, and that attestation windows must be thirty-six times longer than independence assumes. On the reconstruction, WindChain detects six of eight manipulation classes—four of them with recall $\ge 0.99$—at a $1.75\%$ false-positive rate; we also report a camouflage regime defeating every per-record test, and a sustained bias at or below $2.6\%$ that the epoch detector does not see. Consensus performance is modeled, not deployed. WindChain narrows the trust boundary rather than removing it: the guarantee is conditional on an independently certified site reference and on physical calibration of the mast and is best read as an auditable plausibility layer beneath settlement rather than as a trustless one. Full article

Public procurement tenders in Bulgaria are in the focus of public attention, despite the transparency of the process, which is conducted online through the Public Procurement Agency platform, participants require greater trust in the conduct of the procedures themselves, as they are not yet fully automated. Blockchain solutions are used in a wide range of businesses, as they offer transparency of transactions, trust between parties and data immutability and also seem suitable for conducting e-tenders for public procurement. This publication offers a solution based on a private blockchain HyperLedger Fabric, which in terms of structure and functionality builds on the existing solution. It ensures bidder identities are confidential from the unauthorized participants and transparency of the work of administrators in the platform and their actions when changing the status of a public procurement. The proposed blockchain based solution improves the evaluation process, reducing certain technical and human-error risks. The results show that it provides greater transparency and efficiency in the spending of public funds, achieving the set quantitative indicators with automated evaluation and qualitative factors defined in the smart contract. Full article

Agentic artificial intelligence (AI) systems are increasingly deployed across distributed cloud–edge–radio infrastructures, where autonomous agents make decisions with direct operational and economic impact. Smart contracts (SCs) enforce business rules and policies, constraining autonomous actions according to predefined operational intent. As agent autonomy expands across heterogeneous networks, ensuring accountability requires transparency, verifiability, and compliance with SC-defined requirements. To address these challenges, this paper proposes the Agent Governance Framework (AGF), which integrates SC-based governance into agentic AI systems, enabling verifiable accountability through traceable autonomous decisions. Built on European Telecommunications Standards Institute (ETSI) and TM Forum principles, AGF comprises six components: (i) a TM Forum-aligned business support system (BSS); (ii) an agentic AI-enhanced operations support system (OSS); (iii) a Network Resource Operations subsystem; (iv) an Identity and Access Role Manager; (v) a Distributed Marketplace; and (vi) a Traceability and Auditability Registry. Together, these components provide an end-to-end (E2E) traceable architecture, linking each action to the responsible agent and SC. A prototype on a local test network with the evaluation of two complementary network test cases demonstrates the framework’s feasibility, confirms its full traceability and immutability, and highlights AGF’s potential as a foundation for reliable, large-scale agent-based systems in telecommunications networks. The results demonstrate 100% traceability across the E2E governance loop and a minimal latency overhead of 2–4% due to the Traceability and Auditability registry. Full article

Sustainable urban infrastructure increasingly relies on blockchain-secured energy digital twins to improve energy-data verification, transparency, traceability, and trust across construction, operation, certification, and compliance. Yet the prevailing literature still treats these systems primarily as descriptive mirrors of physical infrastructure, emphasizing their ability to capture, verify, and protect data on energy production, consumption, storage, and exchange. Verified records can underpin institutional outcomes such as certification and compliance—but this framing ignores a deeper change: blockchain-secured digital twins may help automate the constitution of those outcomes, rather than only representing infrastructure performance. This conceptual study develops the Automated Constitution Model (ACM), which explains the conditions under which blockchain-secured energy digital-twin records transition from epistemic verification to institutionally recognized outcomes and how accountability is redistributed across the socio-technical actors involved in that transition. The model defines seven interconnected layers: physical infrastructure, measurement, digital representation, cryptographic attestation, rule interpretation and execution, institutional outcome, and legitimacy/accountability. Lower layers are epistemic—they measure, represent, and validate physical energy events. The shift occurs when encoded rule systems, such as smart contracts, certification logic, compliance frameworks, and market-governance protocols, interpret cryptographically attested records to generate recognized institutional outputs such as renewable energy certificates, settlement claims, compliance statuses, payment rights, and ownership records, rendering the higher layers ontological and normative. This study contributes to blockchain governance, digital twins, and sustainable infrastructure research by theorizing blockchain-secured digital twins as systems of automated institutional constitution rather than mere information-integrity tools. It also surfaces a growing accountability gap: as institutional outcomes increasingly rely on encoded rules, platform designers, data modelers, authors of smart contracts, certifiers, and regulators may share accountability with physical actors. Full article

Blockchain-based infrastructures have increasingly been adopted for secure and tamper-resistant management of academic credentials. Despite the advantages offered by blockchain technology, existing blockchain-based credential management systems continue to face several scalability challenges, particularly in terms of limited transaction throughput, increased confirmation delays, and continuous ledger growth resulting from storing individual certificates as separate blockchain transactions. These limitations become more evident in large-scale educational environments where universities and affiliated institutions are required to issue and verify thousands of digital credentials within limited operational timeframes. To overcome these challenges, this work introduces a performance-optimized blockchain architecture for scalable academic credential management. The proposed framework separates certificate preprocessing from blockchain anchoring by incorporating a microservice-based parallel processing layer, Merkle-tree-based batch anchoring, and distributed off-chain storage mechanisms. This modular design reduces blockchain transaction overhead while maintaining the security, integrity, auditability, and verifiability of academic credentials. To assess system performance, a formal analytical model integrating queueing theory and blockchain performance characteristics is developed to characterize system behavior under varying workload conditions. By enabling multiple certificates to be aggregated and committed through a single blockchain transaction, the proposed architecture improves throughput and enhances storage efficiency compared to conventional blockchain-based approaches. Analytical evaluation demonstrates that the system can sustain high certificate issuance rates while maintaining low confirmation latency and minimal on-chain storage growth. Full article

Smart-city services increasingly rely on Internet of Things (IoT) deployments using lightweight Message Queuing Telemetry Transport (MQTT), yet weakly protected systems remain exposed to spoofing, unauthorized state changes, and limited accountability. This work evaluates blockchain and smart contracts as a complementary trust layer for MQTT-based smart-city IoT rather than as a replacement for transport-layer security. The proposed architecture provides owner-controlled device registration, per-sensor nonce management, replay-resistant Elliptic Curve Digital Signature Algorithm (ECDSA) authentication, authorization of state-changing operations, and tamper-evident event logging. MQTT confidentiality remains dependent on Transport Layer Security (TLS) or payload encryption. A prototype was implemented using ESP32 microcontrollers, a Raspberry Pi MQTT broker, Node-RED supervision, MongoDB storage, and Ethereum smart contracts deployed on Sepolia. The evaluation combines practical attack scenarios (unauthorized sensor modification, identity spoofing, and data manipulation) with measurements of blockchain latency, throughput, and gas consumption. Results show auditable nonce-bound signed updates, with mean transaction latency close to 12 s. Because the contract updates one sensor per transaction, costs are interpreted per confirmed write operation and scenario size. The findings position blockchain as an audit and policy-enforcement component for MQTT-based IoT. Full article

Food-safety systems increasingly need to manage large detection files and externally generated analytical results across multiple organizations while linking these records to batch-level control actions. This study proposes a blockchain-based dual-track mechanism for trusted circulation of food-safety detection data and batch-level risk control, using aflatoxin B1 (AFB1) as the empirical case. High-dimensional files are stored in InterPlanetary File System (IPFS) and anchored on-chain by content identifiers (CIDs); three authorized oracles use two-of-three matching of detection values and evidence hashes before contract-based state determination. A stage–device–operation inverted index identifies associated batches, while signed second-track confirmations drive GREEN/YELLOW/RED state transitions. Experiments on a four-node Quorum Byzantine Fault Tolerance (QBFT) network used 57 independent HyperPistachio samples with 86.625-mebibyte (MiB) band-interleaved-by-line (BIL) files. Real-file access was successfully completed, single-oracle failures were tolerated when two consistent oracle reports remained, and associated-batch query latency increased only from 13.06 to 16.78 ms as fanout rose from 1 to 40. A 115.15 min sustained run maintained consistent states across all four nodes. The study manages externally supplied AFB1 results rather than evaluating analytical AFB1 detection accuracy, and its experimental validation is limited to the AFB1 case. Full article

Federated learning (FL) enables collaborative model training without centralizing raw training records, but it does not inherently provide verifiable model provenance, enforceable fairness policies, or auditable control over aggregation. This paper presents FairAI, a blockchain- and IPFS-enabled framework that treats each local model as a governed artifact linked to performance and group-fairness metrics, content identifiers, manifests, Groth16 evidence, and smart-contract decisions. Only models approved on-chain and subsequently retrieved and validated through their registered CIDs are eligible for aggregation. The primary real-data evaluation used the Adult and COMPAS datasets under IID and joint label/protected-group non-IID partitions, with ten paired seeds comparing standard FedAvg, post hoc fairness assessment, a pre-aggregation fairness policy gate, and FairFed. Under heterogeneous Adult data, the policy gate reduced the demographic-parity gap from 0.0273 to 0.0127, while accuracy decreased from 0.7740 to 0.7629. Under heterogeneous COMPAS data, the equalized-odds gap decreased from 0.2262 to 0.1226, while accuracy decreased from 0.6495 to 0.5809; the paired accuracy and equalized odds differences remained significant after Holm correction, with adjusted p-values of 0.0318 and 0.0491, respectively. Additional bounded experiments evaluated a small multilayer perceptron, policy threshold sensitivity, logical-client scaling, poisoning, coordinate-wise median aggregation, two native Kubo/IPFS peers, V2 Groth16 verification, and smart-contract overhead. Thirty valid V2 proofs were accepted, six inconsistent cases were rejected, and direct Solidity verification consumed 348,811 gas per measured transaction. A full-path false-metric experiment showed that the proof verifies threshold compliance and artifact binding for supplied values, but does not establish their correct derivation from private data. When an approved artifact became unavailable, FairAI cancelled the round before aggregation and published no global model. Full article

Blockchain technology (BCT) is often discussed as digital support for timber traceability in the context of the EU Deforestation-Free Products Regulation (EUDR), which requires operators and traders to demonstrate legality, deforestation-free production, geolocation at the forest parcel level, and verifiable supply chain documentation from 30 December 2026, with an extended timeline for micro, small, and medium-sized enterprises (SMEs) until 30 June 2027. This study assesses where BCT can realistically add value in timber supply chains under operational forestry conditions and identifies the necessary technical, organizational, and legal prerequisites. A combination of a targeted literature review and empirical input from experts in the forestry and timber industry, including guided expert web-conferencing interviews (n = 41), an online survey (n = 69 completed responses), and a transdisciplinary workshop (n = 18) was utilized to obtain a comprehensive overview of industry perspectives. Qualitative data from interviews and workshop sessions were analyzed using structured qualitative content analysis, while survey data were evaluated using descriptive statistics. The expected benefits are associated with the introduction of tamper-proof timber harvesting practices and cross-organizational verification mechanisms. To address the discrepancy between biological uncertainty and digital rigidity, the study proposes a dynamic allocation model adapted from the energy sector that distinguishes between fixed and variable wood capacities to automate logistical planning via smart contracts. However, respondents emphasize that practical obstacles, such as limited digital maturity in forestry, fragmented data infrastructures across the supply chain, and unresolved issues of data sovereignty hinder the implementation of BCT. BCT alone is unable to resolve the problem of weak physical-digital identity continuity, a phenomenon widely known as the oracle problem; however, coupling the ledger with physical or biological anchors (e.g., photo-optical, automated inkjet marking identification) can re-establish this physical–digital continuity and thereby resolve the oracle problem. The results demonstrate that blockchain acts most plausibly as a supporting component within hybrid traceability architectures that prioritize event-based authentication, off-chain data processing where appropriate, and integration with existing certification systems. The study highlights the necessity of defining distinct organizational roles and responsibilities while integrating user-centric digital solutions tailored specifically to small and medium-sized enterprises (SMEs). Full article

Cyber–physical systems (CPSs) increasingly rely on complex software components whose vulnerabilities may affect both digital services and physical processes. Fuzzing is a practical technique for discovering such vulnerabilities in CPS-facing parsers, protocol handlers, and edge services. Distributed fuzzing improves throughput, but outsourcing fuzzing tasks to multiple untrusted nodes introduces privacy risks: valuable seeds, especially crash-triggering samples, may reveal vulnerability information before affected users are protected. In this paper, we propose PrivFuzz, a privacy-preserving collaborative fuzzing framework. PrivFuzz allows organizations and individuals to collaborate and receive rewards while keeping fuzzing seeds confidential and enabling controlled encrypted seed reuse among untrusted fuzzing nodes. The key idea is to combine trusted execution environments (TEEs) with blockchain-based smart contracts to support confidentiality and fair reward settlement. We give game-based definitions and reduction-style arguments for seed confidentiality, worker soundness, outsourcer atomicity, and duplicate-claim resistance under an attested execution model. We implement a PrivFuzz prototype and evaluate it on four open-source parsing targets. Separately, native AFL++ sanity checks suggest that CPS-facing industrial protocol parsers such as Modbus and OPC UA fall within the same fuzzable target domain. Demonstrating end-to-end PrivFuzz on CPS control programs is left as future work. Using PrivFuzz, we discovered nine bugs and reported them to the developers. Full article

Blockchain is one important building blocks of the Internet of the future, called Web3. The Blockchain technology supports a wide range of applications, spanning from Smart Cities and automotive industries, from agriculture to energy. The healthcare sector, in particular, has experienced a profound impact from blockchain-based technologies, paving the way for the development of true digital healthcare systems. By enabling secure and immutable data storage, and facilitating the sharing of this information among all nodes possessing a local copy of the distributed ledger, blockchain plays a vital role in the analysis of healthcare data. This paper provides a comprehensive survey of the main blockchain platforms utilized in the digital healthcare, integrated with a comparative analysis. In addition, the implementation of Innovative permissioned Blockchain for eHealth (IBEH) is presented and discussed in detail. IBEH addresses key challenges in digital health data management, including secure and controlled access to sensitive health information, ensuring data integrity and traceability, and secure sharing between different healthcare institutions and organizations. This is made possible by decoupling the application and blockchain layers and by a flexible, customizable, and easily deployable infrastructure. IBEH integrates the application-oriented and embedded layer with that of a blockchain network built with the MultiChain platform, which uses smart contracts with permissions, REST APIs, and RPC calls. The main features and its associated smart contracts within the healthcare domain are discussed. Finally, the analysis of performance is provided. Full article