Blockchain Papers

Shilpa R. V., Malatesh S. H.

Secure and transparent attendance management has become increasingly important in educational institutions as conventional attendance systems often face challenges such as proxy attendance, unauthorized record modification, and limited traceability. Most existing solutions rely on centralized databases, making them susceptible to data tampering, accidental loss, and single-point failures. This paper presents a Blockchain-Based Attendance Management System that leverages blockchain technology to provide a decentralized and immutable mechanism for recording and verifying attendance information. The proposed framework integrates a React.js-based user interface with a Node.js and Express.js backend, while Firebase Authentication and Firestore manage user authentication and application data. Attendance records are securely stored through Ethereum smart contracts executed on the Ganache blockchain network, with transaction hashes linked to Firebase for efficient retrieval and verification. This hybrid architecture combines the scalability of cloud-based data management with the integrity and transparency of blockchain technology. Once attendance is recorded, the information cannot be altered without detection, ensuring reliable auditability and improved trust among students, faculty members, and administrators. The implemented system demonstrates secure attendance recording, fast verification, and efficient transaction management while reducing the possibility of record manipulation. The proposed solution offers a practical, scalable, and cost-effective approach for modern attendance management and provides a strong foundation for future enhancements such as biometric authentication, QR code-based attendance, and cloud-enabled blockchain deployment.

D. Monica, Malatesh S. H.

The rapid growth of digital education and online recruitment has significantly increased the demand for reliable academic credential verification. Conventional certificate verification methods are often centralized, time-consuming, and susceptible to document forgery, unauthorized modification, and administrative delays. To address these challenges, this paper presents a Blockchain-Enabled Decentralized Framework for Secure Academic Certificate Issuance and Real-Time Verification. The proposed framework utilizes Ethereum blockchain technology through Solidity smart contracts to establish an immutable and transparent repository of certificate records, ensuring that issued credentials cannot be altered without detection. A SHA-256 cryptographic hashing mechanism is employed to generate unique digital fingerprints for each certificate, while Firebase Authentication and Cloud Firestore provide secure identity management and efficient off-chain metadata storage. The user interface is developed using React.js, enabling educational institutions to issue certificates and allowing employers, universities, and other stakeholders to verify credentials instantly through a simple web-based platform. During verification, the system recomputes the certificate hash and compares it with the blockchain record to detect tampering and validate authenticity in real time. Experimental evaluation on a local Ethereum network demonstrates reliable certificate issuance, rapid verification with sub-second response times, secure transaction handling, and effective resistance against certificate forgery. The proposed framework enhances transparency, trust, and operational efficiency while minimizing manual verification efforts. Furthermore, its modular architecture facilitates future migration to public blockchain networks and decentralized storage platforms, making it suitable for scalable deployment across educational institutions and digital credential ecosystems.

Staley Ian

Pipelines that pair a large language model with a static analyzer, feeding findings back as repair instructions, appear throughout recent smart contract repair research. They rest on a rarely examined assumption: that the analyzer output serving as the oracle faithfully records what the analyzer found. I report three ways that assumption fails, identified during a four-contract instrument-validation exercise preceding a planned repair study. First, Mythril v0.24.8 can exit without reaching the analysis phase while returning exit status zero, empty standard error, and a findings array byte-identical to that of a genuinely clean scan; the failure is reported in a sibling JSON field that finding-extraction code has no reason to read. Second, 12 of 23 Slither findings in my validation set fell outside the high, medium, and low impact bands, so an unfiltered count measures a composite whose components may not behave alike under repair. Third, keying finding identity on source location breaks across repair rounds. On the one contract carried through three rounds, location-based keying inflated resolved findings from 7 to 12 and introduced findings from 2 to 7. The underlying instability is established in the warning-tracking literature; my contribution is its consequence for repair metrics, where it biases both transition counts upward and can confound comparison between methods producing differently sized .patches. I separately report an executed exploit showing a specification-level authorization defect that produced no high or medium impact finding. I propose calibration procedures for each hazard and release the harness, contracts, and raw analyzer output at doi:10.5281/zenodo.21586404.

Samseer R. H., Asokan Vasudevan, Sheiladevi Sukumaran, Kalimbetov Xaliknazar · 6 authors

This paper develops a Quantum-Institutional Automated Negotiation (QIAN) algorithm as an intelligent decision support system for carbon credit markets, contributing to quantum game theory applications in automated negotiation and institutional decision-making. We extend the Eisert–Wilkens–Lewenstein (EWL) framework by introducing an Institutional Filter Function Φ_C that maps continuous quantum strategies—phase shifts and superpositions—onto finite, legally viable contract archetypes. This filter models regulatory, political, and organizational constraints that collapse the infinite quantum strategy space into a tractable finite set, enabling computationally efficient decision support. We prove convergence of the automated negotiation algorithm to a Pareto-superior Nash Equilibrium and demonstrate, through Monte Carlo simulation with literature-calibrated parameters, that the collapsed quantum equilibrium yields a mean joint utility uplift of 13.5% over classical cooperation (95% CI: 9.8%–17.3%, p < 0.001), with the upper bound reaching 17.3% and 26.8% of simulations achieving uplifts in the 15–30% range. The framework maps directly to blockchain-based smart contracts, providing a deployable mechanism for sustainable carbon markets that aligns with SDG 13 (Climate Action) and SDG 17 (Partnerships). This work advances quantum game theory from abstract formalism to computational institutional design, offering a novel decision support approach for negotiation analysis under real-world constraints.

Varun Kesavan, Aruna Polisetty, Rajkumar Subbaiyan

Decentralised finance (DeFi) is a relatively new trend in finance that uses blockchain, smart contracts, and distributed ledger technology to offer financial services in a decentralised manner. Although scholars have made many theoretical advances in decentralised finance in recent years, knowledge of its theoretical structure and future research areas remains limited. This is why this study provides a bibliometric analysis of 1002 articles on DeFi published in Scopus between 2012 and 2026. The analysis uses performance analysis and a science mapping approach based on citation analysis, co-authorship, bibliographic coupling and keyword co-occurrence analysis. The results reveal a remarkably high annual growth rate of 39.34% and DeFi’s dynamism and interdisciplinary nature. The three main countries involved in DeFi research are the USA, China, and the UK. Management Science, Energy Economics and Technological Forecasting and Social Change became the main scientific journals for disseminating knowledge about DeFi. Analysis of thematic changes showed a transition of scientific interests from blockchain and cryptocurrencies to new topics, like artificial intelligence, sustainability, governance, and financial inclusion. Overall, the current study provides a better understanding of the intellectual, conceptual, and social basis of DeFi and highlights possible research areas in the use of artificial intelligence in DeFi, decentralised governance, and sustainable digital financial system development.

Dileep Kumar Murala, G. Siva Krishna, P. N. V. M. Syamala Rao, Madhusudana Rao Nalluri · 5 authors

Integrating blockchain technology with cloud computing has enabled Blockchain as a Service (BaaS), a cloud-based paradigm that allows users to design, deploy, and manage customized blockchain applications, including smart contracts and domain-specific business functionalities. BaaS providers manage infrastructure provisioning, maintenance, and scalability while ensuring quality of service (QoS) compliance through service level agreements (SLAs). However, existing resource management approaches often struggle to satisfy dynamic performance requirements in a cost-efficient manner without increasing operational overhead or reducing provider efficiency. This paper presents a structured Adaptive SLA-based assistance framework for deploying Hyperledger Fabric on cloud platforms. The framework integrates automated performance monitoring using Hyperledger Caliper, SLA violation detection through programmed SLA chaincode, and automated VM scaling via the OpenStack4J API within a 3E (effective–efficient–economical) verification methodology. A greedy multi-objective scheduling mechanism guides parameter optimization by selecting scaling actions according to marginal performance gain per unit cost. Experiments were conducted on the Nectar Research Cloud using Hyperledger Fabric 2.5 to evaluate the impact of VM size, block size, peer count, and storage configuration on throughput (TPS) and average latency. Results demonstrate that the framework consistently achieves performance targets of 50%, 100%, and 200% above the baseline configuration through adaptive resource reconfiguration. Among evaluated strategies, Comb2, which combines dual block size adjustment with VM scaling, emerged as the optimal balanced configuration in terms of performance and cost efficiency. While automated monitoring, SLA enforcement, and VM scaling are fully implemented, continuous online scheduling under dynamically changing workloads remains future work. The proposed framework establishes a practical foundation for SLA-driven blockchain optimization in cloud environments and supports future extensibility to additional BaaS platforms.

Ria Bandyopadhyay, Jeet Sadhukhan, Supratik Chakraborty, Pratyush Mishra · 6 authors

The construction industry faces several difficulties in warehouse management along with construction industry&s;s supply chain that is characterized by complex, multi-tiered interactions involving material suppliers, transporters, contractors, and on-site project managers. Traditional management systems suffer from delayed information exchange, lack of transparency, and vulnerability to fraud or errors, often leading to cost overruns and schedule delays. The purpose of the current paper is to suggest an Artificial Intelligence of Things (AIoT) and blockchain-based supply chain management model to be used in the construction industry. AIoT involves the use of IoT devices or RFID tags, GPS trackers, and environmental sensors along with AI algorithmic methods to conduct predictive analytics, anomaly detection, and automated decision-making in the edge or the cloud. Blockchain technology offers the benefit of immutable and transparent records that cannot be altered and is tamper resistant, which facilitates trust among the distributed stakeholders and automates the workflows of the contract through the use of smart contracts. The architecture that is proposed has three layers: 1 AIoT real-time data acquisition sensing and analytics, 2 Secure data storage blockchain ledger and smart contract execution, and 3 A stakeholder application dashboard. In order to test our framework, we conducted a simulation of a scenario with prefabricated steel parts as supply. We determined the effectiveness of the system in tracking items, recording events as swiftly as possible, the security of the process and the efficiency of the whole process. The findings were also staggering: the accuracy of the tracking increased by 92 percent, the reporting is 58 percent quicker, and the prevention of fraud is much more robust than the traditional ERP systems. Such results demonstrate that the convergence of the AIoT and blockchain technologies can contribute to the solution of current issues in the supply chain in construction, which will result in the improved and more data-driven project management. Second, we will experiment with this approach through real life projects and how it could be used with Building Information Modelling (BIM) platforms.

Murugeshwari B., Kayalvizhi S, Daya Florance D, Saranya S

To deploy deep learning-based diagnostic systems in a clinical setting, they need to have not only a high degree of predictive accuracy, but also an unbroken cryptographic chain to prove that the model parameters have not been changed from one inference to the next. This incompatibility arises because softmax, GELU activation, and layer normalization involve transcendental operations to produce the final output. Transcendental operations cannot be represented over the prime finite fields that are necessary when utilizing Rank-1 Constraint Systems (R1CS). The work here provides a mathematically sound approach to resolving the incompatibility by providing three formally defined polynomial approximations: a degree-3 Taylor series softmax approximation (ε ≤ 2.47E-03 per weight); a degree-5 composite polynomial GELU (ε ≤ 1.80E-03); and a squared witness hint reformulation of layer normalization that results in exact constraint satisfaction. The accumulating polynomial approximation errors across 12 transformer encoder blocks have a total approximation error defined as (ε total ≤ 0.0512) and results in a loss of less than one-fifth of a percent in accuracy (94.1% vs. 94.3%) on the RSNA Pneumonia Detection benchmark. The entire ViT-B/16 inference model was compiled into an R1CS form of approximately 2.3×10⁸ R1CS constraints and instantiated as a Groth 16 zk-SNARK. The integrity of the model is confirmed by hashing the parameters using SHA-256 onto an immutable Polygon zkEVM smart contract, allowing for on-chain verification of inference without revealing any of the proprietary model weights. Additionally, this system produces an area under the receiver operating characteristic curve (AUC-ROC) of 0.961, a mean latency for proof generation of 2.84 seconds, an end-to-end verification time of 5.07 seconds, and an average cost for on-chain verification of 0.012ETH, all within the operational constraints of typical radiology workflows.

Keisuke Suzuki

What is real has always been something we find , not something we make —or so philosophy has assumed. This paper argues otherwise. Characterizing reality through resistance rather than substance (the ways the world refuses a subject’s mastery), I distinguish three modalities correlative to epistemic, judgmental, and practical mastery: Substrate (matter’s resistance to representation), Contingency (the forceful givenness of experience that resists revision by judgment), and the Inexorable (structures’ resistance to intervention). Treating virtual environments, AI agents, and blockchain smart contracts not as proofs but as revelatory cases, I show that technology now extends the latter two modalities, Contingency and the Inexorable, artificially. The result is the paper’s central concept, Artificial Externality : human-made structures whose resistance to intervention is deliberately engineered to be practically insurmountable, even for their creators, and that thereby acquire an externality once attributed only to nature. Absoluteness, traditionally found, can now be produced. I close by drawing out the stakes for consciousness: our criteria for what counts as real quietly shape our criteria for what counts as conscious.

Muhammad Ali Hassan Ahmad, Muhammad Hashim Ali, Muhammad Ali Amer, Muhammad Naiman Jalil · 6 authors

A blockchain is a decentralized, secure ledger system that enables transparent and immutable record-keeping, essential for trust and security in digital transactions. Smart contracts are self-executing agreements encoded on a blockchain, enabling different parties to fulfill the terms of the agreement automatically. These contracts trigger corresponding actions when conditions are met, ensuring decentralized and transparent transactions. Writing reliable smart contracts is challenging due to the lack of standardization. To find security vulnerabilities, tools based on various approaches, including symbolic execution, are used. However, these tools often report a large number of false positives, raising concerns about their reliability. The time and effort spent investigating false positives diverts resources from addressing actual vulnerabilities. Therefore, such tools must also be evaluated according to the rate of false positives they exhibit. More importantly, the algorithms and heuristics used by the tools must be enhanced to distinguish between true vulnerabilities and false alarms. In this paper, we first demonstrate the prevalence of false positives in vulnerability reports generated by Mythril, a symbolic execution-based analysis tool for Ethereum smart contracts. We analyze the root causes of these inaccuracies and devise a rule-based approach based on the gained insight to reduce false positives. We implement our rules for the most impactful vulnerabilities in Mythril and assess the effectiveness of our approach. Our results show a significant reduction in false positives without compromising the detection of true vulnerabilities, thus enhancing the tool's reliability.

Kundan Mukhia, Sabat Rai, Vivek Shrivastav, Imran Ansari · 5 authors

Stablecoins have rapidly emerged as an important class of digital assets and a component of the digital financial ecosystem. Despite their growing importance, the statistical properties of stablecoin transaction activity remain largely unexplored. To the best of our knowledge, this is the first study to investigate scaling behavior in stablecoin transaction data, focusing on USDT and USDC. We analyze approximately 370 million USDT and USDC transactions recorded on the Ethereum blockchain across six periods spanning June 2024 to February 2026. Based on interactions between Externally Owned Accounts (EOAs) and Smart Contracts (SCs), we classify transactions into four categories: EOA-EOA, EOA-SC, SC-EOA, and SC-SC. Using maximum-likelihood estimation of power-law exponents, we find that transaction value distributions exhibit heavy-tailed scaling for both stablecoins across all periods and interaction categories. We identify two distinct scaling regimes: EOA-involved categories cluster around 1.45-1.60, whereas SC-SC transactions exhibit higher exponents of approximately 1.72-1.73. Sensitivity analysis confirms that this separation is robust across periods, stablecoins, and fitting sample sizes. Counterfactual analysis shows that changes in category weights alone cannot explain the observed variation in the overall exponent. Across different sample sizes, the counterfactual path accounts for only about 10%-35% of the total temporal range observed in the actual data. Overall, our results indicate two broadly differentiated scaling regimes in the tail of stablecoin transaction values. Power-law tail behavior is observed throughout stablecoin transaction activity, but the exponent depends on whether transactions are driven by EOAs or SCs. These findings provide a basis for further research on scaling behavior and transaction heterogeneity in blockchain-based financial systems.

T. O. Folorunso, W. A. Sanusi, H. Afia

Abstract Nigeria, a leading natural gas producer in Africa, faces significant challenges in optimising its gas infrastructure to support efficient commercialisation, reduce resource wastage, and foster transparency in transactions. Current systems for custody transfer, contract enforcement, and payment reconciliation often suffer from inefficiencies, manual interventions, and lack of trust among stakeholders. This paper proposes a novel technical framework that leverages Blockchain and the Internet of Things (IoT) to address these challenges by digitalising the country's gas pipeline network. The proposed framework deploys IoT-enabled smart sensors at key custody transfer points across the gas supply chain to monitor critical parameters such as gas flow rate, volume, temperature, and pressure in real time. These parameters are securely stored on a blockchain network, ensuring data immutability, transparency, and auditability. Smart contracts integrated into the blockchain enable automated execution of contractual terms, including the initiation of payment processes via Enterprise Resource Planning (ERP) systems once predefined conditions—such as the transfer of an agreed gas volume—are met. This system minimises delays, mitigates risks of data tampering, and eliminates disputes between producers, suppliers, off-takers, and consumers by providing a single source of truth. Furthermore, the framework supports smaller producers by enabling fair participation in the market and providing a mechanism to monetise flared gas. The paper outlines the technical architecture of the proposed solution, including blockchain consensus mechanisms, IoT device integration protocols, and cybersecurity safeguards tailored to the Nigerian context. To validate the feasibility of this approach, the study examines key implementation considerations, including regulatory compliance, scalability, and integration with Nigeria's existing gas infrastructure. A comparative analysis with similar initiatives globally was conducted to highlight best practices and lessons learned. By demonstrating the potential for enhanced efficiency, accountability, and economic growth, this paper provides a robust pathway for transforming Nigeria's gas sector through advanced digital technologies.

Novan Ilham Ramadhan, Rizky Parlika, Ardhon Rakhmadi

Electronic voting (e-voting) systems continue to face challenges related to transparency, result validation, and duplicate voting prevention. Blockchain technology offers characteristics such as decentralization, transparency, and immutability that can support more auditable voting processes. This study presents a prototype implementation of a blockchain-based e-voting system using Ethereum smart contracts to support transparent vote recording, public auditability, and wallet-level double voting prevention. The system was implemented using Solidity-based smart contracts deployed on the Ethereum Sepolia Testnet and integrated with MetaMask for transaction authentication. Smart contracts manage election creation, candidate registration, voter registration, vote recording, duplicate vote prevention, and voting result finalization. An audit trail mechanism was implemented to allow voting activities and transaction records to be publicly verified through the Etherscan blockchain explorer. All predefined functional testing scenarios were executed successfully. The evaluation results indicate an average gas usage of 75,109 gas, an estimated transaction cost of 0.000113 ETH, and a transaction latency of approximately 4–5 seconds. The implemented wallet validation mechanism and hasVoted mapping effectively prevent duplicate voting attempts associated with the same wallet address. However, the proposed system represents a prototype-level evaluation conducted on the Ethereum Sepolia Testnet and does not provide voter identity verification, ballot anonymity, or real-world election readiness. The findings demonstrate the feasibility of Ethereum smart contracts for transparent auditability and wallet-level double voting prevention in blockchain-based voting environments.

Tapasi Bhattacharjee, Amalendu Singha Mahapatra, Dipika Pramanik

Educational crowdfunding has emerged as a promising approach to provide educational resources to underprivileged communities. Conventional systems often suffer from a lack of transparency, weak accountability, inefficient allocation of funds, and inadequate traceability of resource use. To address these issues, the present study proposes an intelligent and efficient educational supply chain management system, “EduDonateBlock.” It uses a blockchain-based crowdfunding framework to ensure transparency, accountability, and efficiency. Decentralization, immutability, and verifiable transactions are supported in educational campaigns. The entire workflow is decomposed into modular smart contracts. These are the identity and access contract (IAC), campaign and donation contract (CDC), verification and allocation contract (VAC), and supply chain and tracking contract (SCTC). These contracts are designed to ensure traceability, accountability, and efficient resource allocation among donors, educational institutions, and administrators. The mathematical framework of EduDonateBlock determines the optimal level of blockchain transparency. This minimizes the Total Expected Cost (TEC) of smart-contract operations. Numerical analysis identifies an optimal transparency level of 87.16% on-chain integration. This finding underscores the economic trade-off between transaction costs and the benefits of automation, operational efficiency, and reduced fraud risk. The proposed framework achieves a campaign success probability of 89.45% and an institutional payoff of Rs. 11,335.99. Furthermore, executing smart contracts requires 0.0044 ETH, and the average latency remains at 6.25 s. The simulation results show that EduDonateBlock offers a more efficient, reliable, and transparent solution for decentralized educational crowdfunding and socially impactful digital supply chains.

Nima Asadi Azizabadi

The expansion of blockchain technology and the evolution of digital platforms have led to the emergence of new concepts in contractual relations, of which "smart contracts" are among the most significant. These contracts are designed as blockchain-based computer programs that execute the terms of the parties' agreement in the form of digital codes and enable the automatic performance of obligations without the need for traditional intermediaries. Such features have increased the speed, transparency, and efficiency of transactions. However, the introduction of this technology into the field of contract law has raised fundamental questions regarding the legal nature, validity, and enforcement of such contracts in various legal systems, particularly those based on classical traditions. The aim of this research is to elucidate the legal nature of smart contracts and analyze the challenges of their enforcement in the Iranian legal system. The research method is descriptive-analytical, and data have been collected through library studies and the examination of domestic and international legal sources. Additionally, with a comparative approach, some legislative experiences of other countries in this field have been examined. The findings indicate that, despite technical differences, smart contracts can be analyzed within the framework of general contract rules. The principle of party autonomy and Article 10 of the Civil Code provide the capacity to accept this type of contract, and the Electronic Commerce Law, by recognizing data messages and electronic signatures, has established a basis for the validity of digital transactions. However, challenges such as ascertaining the true intent of the parties, determining liability for technical errors, and the conflict between the immutability feature of blockchain and institutions such as rescission and mutual rescission persist. Accordingly, the formulation of supplementary regulations, the development of legal infrastructure, and the enhancement of specialized knowledge appear essential for the safe and effective utilization of this technology.

Ch Nanda Krishna, S.J.R.K. Padminivalli V, Aravapalli Rama Satish, Kondragunta Rama Krishnaiah · 6 authors

No abstract is available for this record.

Abdul Adlim, Babun Suharto, Wildan Khisbullah Suhma, Kholida Ulfi Mubaroka

The rapid development of crypto assets has challenged the classical concept of mal (property) in Islamic jurisprudence because digital assets do not possess tangible physical characteristics traditionally associated with lawful ownership. This study aims to reconstruct the paradigm of mal within contemporary fiqh by examining the legal status of crypto assets through the framework of maqasid al-shari'ah, particularly hifz al-mal, while evaluating the role of smart contracts in reducing contractual uncertainty (gharar). This study employed a qualitative normative legal approach based on literature analysis of classical fiqh, usul al-fiqh, contemporary Islamic legal scholarship, institutional fatwas, and financial regulations. The findings demonstrate that the concept of mal has evolved from a material-based understanding toward a value-oriented paradigm that emphasizes recognized benefit, scarcity, and lawful ownership. Under these criteria, crypto assets may be recognized as mal when supported by legitimate ownership, transparent governance, and productive economic purposes. Smart contracts contribute to minimizing contractual and operational gharar through automated execution and transaction transparency, although they cannot eliminate risks arising from market volatility. This study proposes a reconstructed paradigm of mal that provides a more contextual analytical framework for assessing the legality of digital assets within contemporary Islamic law.

Faizah Alsulami

This study examines the current state of digital asset auditing and proposes a clearer future vision through a systematic review of relevant literature and prior studies. It highlights the fundamental differences between digital and traditional assets, explains the classification of digital assets and their close association with blockchain technology, and analyzes the existing accounting and auditing frameworks considering international standards and provides a brief overview of the status of Egyptian legislation. The study also discusses the evolving role of auditors and the main stages of the audit process in the digital environment. The findings indicate that rapid digital transformation requires the development of advanced auditing standards and methodologies, and that the adoption of data analytics, smart contracts, and continuous auditing, together with enhancing auditors’ technical and professional competencies, contributes to improving audit quality, transparency, and risk management related to digital assets.

Pravin R Pachorkar

Online voting platforms that rely on classical cryptography and centralized trust anchors face escalating challenges as the demand for secure and transparent digital elections grows. Such systems remain exposed to quantum-era threats, insider manipulation, and delayed audit mechanisms, which together can undermine public confidence and electoral legitimacy. To counter these risks, a quantum-resistant, multi-layer blockchain architecture has been developed to enable remote voting with continuous verifiability and resilience. This architecture resolves key weaknesses through five integrated layers. Quantum-Resistant Distributed Ledger Initialization (QR-DLI) embeds lattice-based cryptography, specifically Kyber and Dilithium variants, directly within the genesis block, ensuring the ledger is tamper-proof from inception and immune to quantum brute-force attacks. The Self-Adaptive Smart Contract Governance Engine (SASCG) introduces dynamic, participation-aware rule adjustments, allowing principled governance without manual overrides and ensuring that voting periods and eligibility rules adapt securely in real time. Homomorphic Vote Encryption with Multi-Authority Shard Key Distribution (HVE-MASKD) guarantees ballot confidentiality and authenticity by combining fully homomorphic encryption with distributed key shares, eliminating single points of trust. The Zero-Knowledge Proof–Based Real-Time Audit Layer (ZKP-RTAL) continuously validates ballot integrity while concealing vote content, creating a public and immutable audit trail. Finally, the Federated Performance & Threat Intelligence Optimizer (FPTIO) aggregates live telemetry and historical attack data to proactively tune consensus parameters and predict potential intrusions without interrupting the election process. Collectively, these layers achieve sub-second cryptographic operations, transaction throughput exceeding 1,500 TPS, over 99 % fraud detection accuracy, and strong scalability. The model provides a future-ready, auditable replacement for current e Voting infrastructures, strengthening digital democracy through post-quantum security, adaptive governance, and intelligent, continuous optimizations.

MARBIYAT TAHIR GIDADO, BASHIRU ABDULGANIYU, MOHAMMED NASIR MUSA, Umaru Umaru

The increasing digitalization of smart grids has significantly improved the efficiency, reliability, and sustainability of modern power systems. However, the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and cloud computing, has introduced new cybersecurity vulnerabilities that threaten critical energy infrastructure. This study presents a blockchain-enabled privacy-preserving Artificial intelligence framework designed to enhance cybersecurity in smart grid environments, with a particular focus on Northeast Nigeria as a case study. The framework integrates blockchain technology, federated learning, differential privacy, edge computing, and artificial intelligence (AI)-driven intrusion detection into a unified architecture to provide secure, intelligent, and privacy-aware protection for smart grid systems. The proposed framework was developed using the design science research methodology and evaluated through simulation and comparative performance analysis. The framework achieved excellent detection performance with an accuracy of 96.8%, precision of 95.9%, recall of 96.4%, and F1-score of 96.1%, significantly outperforming conventional centralized AI and blockchain-only approaches. The integration of federated learning and differential privacy effectively protected consumer information with a privacy leakage rate of only 2.7% while maintaining high model utility of 94.8%. The blockchain performance evaluation showed a transaction latency of 184.6 Ms, a throughput of 421.3 transactions per second, and efficient smart contract execution. The suitability of the framework for practical deployment with moderate resource requirements by computational assessment. The findings demonstrate that combining blockchain, privacy-preserving learning, and AI provides a comprehensive, scalable, and resilient cybersecurity solution for SGIs. This study contributes to the growing body of knowledge on smart grid cybersecurity and offers practical insights for utility providers, researchers, and policymakers seeking to strengthen the security and resilience of emerging smart grid systems, particularly in developing regions with infrastructural challenges.

Muhammad Dzikri Abadi, Roudlotul Badi’ah, Dadang Wiratama, Ika Purwanti · 7 authors

This study maps the development, collaboration patterns, citation structure, and thematic evolution of research on blockchain technology in the waqf sector. A bibliometric analysis of 417 Scopus-indexed publications published from 2006 to 12 July 2024 was performed using Bibliometrix in RStudio and VOSviewer. The analysis covered publication trends, influential sources and contributors, country productivity, citation impact, collaboration networks, and keyword co-occurrence. The results show increasing scholarly attention to the intersection of blockchain, Islamic finance, fintech, and waqf management. Malaysia and Indonesia emerged as the most productive and most cited countries, while an international co-authorship rate of 29.74% indicated moderate cross-border collaboration. Keyword analysis revealed that the field is anchored in Islamic finance, fintech, blockchain, and waqf, with growing attention to cash waqf, crowdfunding, financial inclusion, digital transformation, smart contracts, cybersecurity, and technology adoption. However, these patterns demonstrate scholarly attention and thematic associations rather than empirical proof of blockchain’s operational benefits in waqf institutions. This study identifies priority gaps in empirical implementation, Shariah governance, stakeholder adoption, technical feasibility, and socioeconomic impact evaluation of blockchain-enabled waqf systems.

Balireddi Durga Anuja, Suneetha Eluri

Blockchain interoperability remains a major challenge because heterogeneous blockchain networks cannot securely and efficiently exchange cross-chain data and transactions. Existing interoperability solutions often rely on central relays or trusted intermediaries, creating security vulnerabilities, limited fault tolerance, and a single point of failure. To address these limitations, this paper proposes VeriMesh, a decentralised mesh-based interoperability framework that combines trust-adaptive routing, multi-path relay verification, and Zero-Knowledge Proof (ZKP)-based validation for secure cross-chain communication. VeriMesh models relay nodes as a trust-weighted graph in which routing decisions dynamically adapt based on node behaviour and delivery reliability. Multi-path routing improves resilience against adversarial relay nodes, while transport-layer ZKP verification enables privacy-preserving validation without exposing sensitive information. The framework was implemented using Python relay nodes, Solidity smart contracts, and an Ethereum (Ganache) environment. Experimental evaluation using structured event-driven workloads demonstrated stable latency below 34 ms and delivery success rates above 85% up to 40% malicious node presence. Comparative evaluation against single-path and random multi-path relay baselines showed improved fault tolerance and routing reliability. The results demonstrate favourable scalability and robustness within the evaluated network range ( N = 10–30), while larger-scale evaluation remains future work. All experiments were conducted in a controlled local Ganache blockchain environment rather than on a public Ethereum testnet or mainnet, so the reported latency, gas, and delivery figures characterise protocol-layer behaviour under controlled conditions and should not yet be interpreted as representative of performance under public-network conditions such as real gas markets, block propagation delays, or network congestion.

Jia Liu, Yuemiao Wang, Chuangchuang Zhu

The increasing demand for trustworthy and privacy-preserving credit reporting systems has exposed the limitations of both centralized and existing blockchain-based solutions, including scalability bottlenecks, weak privacy protection, and insufficient incentive mechanisms. To address these challenges, we propose LightCred, a novel consortium blockchain-based personal credit management framework that integrates lightweight nodes, Merkle proofs, multi-role smart contracts, and privacy-preserving cryptographic techniques. LightCred features a five-layer architecture that efficiently collects, verifies, stores, and serves credit data while ensuring data integrity, confidentiality, and regulatory compliance. Specifically, it (i) employs a low-cost and traceable data reduction mechanism through lightweight nodes and Merkle proofs to minimize storage and improve verifiability; (ii) introduces a multi-role smart contract model that enforces dynamic access control and fair incentive distribution based on participant reputations; and (iii) integrates zero-knowledge proofs and homomorphic encryption to support privacy-preserving credit scoring and querying. Experimental results demonstrate that LightCred achieves superior performance compared to five baseline methods, delivering up to 5% higher throughput, 3–5% lower privacy leakage, and 10–15% reduced storage costs, while maintaining competitive latency and auditability. These findings validate LightCred as a robust, scalable, and privacy-aware credit management solution, offering a viable alternative for modern credit reporting systems.

Oliviani Yanto, Indirani Wauran

This study aims to analyze the alignment of Indonesia’s regulations on electronic contracts with the UNCITRAL Model Law on Electronic Commerce in order to promote reforms to contract law that are more adaptable to digital developments. The digital transformation has made electronic contracts the primary means of conducting cross-border civil transactions. However, Indonesia’s regulations under the ITE Law are considered to be limited to business transactions and do not yet accommodate other civil relationships. The method used is normative legal research employing legislative, conceptual, and comparative approaches. This study analyzes the UNCITRAL Model Law on Electronic Commerce as an international legal instrument serving as a guideline for harmonization. In addition, this study also examines the ITE Law and its implementing regulations as sectoral regulations, as well as the Indonesian Civil Code as the general legal framework that should ideally serve as the overarching regulatory framework for electronic contracts. The novelty of this study lies in its analysis of the relationship between the principle of freedom of contract in the Indonesian Civil Code and UNCITRAL’s international standards, a topic rarely discussed in the national literature. The results of the study indicate that the UNCITRAL Model Law provides a flexible and universal framework consistent with the principle of freedom of contract; however, its application in Indonesia remains limited by the ITE Law’s focus solely on electronic transactions. The conclusion of this study is that harmonization of Indonesian contract law with international principles is necessary so that the regulation of electronic contracts can apply across sectors, not limited to business, and meet the dynamics of legal globalization.