Stephen Oko Gyan Torto, Rupendra Kumar Pachauri, Jai Govind Singh, Shubham Tiwari ¡ 7 authors
Global projects are mobilizing technologies to fight power generation curtailment and smooth demand by exploiting excess energy via transactive energy management and control. Sharing and transferring energy between microgrids helps manufacturers and businesses create energy autonomously. The transition to Multi-Vector Multi-Agent Energy Systems (MMV-ES) demands a paradigm shift from traditional centralized control to decentralized, market-based coordination. Transactive Energy Management (TEM) has emerged as a key enabler in this context, supporting local flexibility, peer-to-peer (P2P) trading, and integrated energy vectors across distributed assets. This review systematically decomposes and classifies the existing state of TEM from several perspectives: the market topology, the interaction of the agent, game-theoretic models and the real deployment challenges. Moreover, two game-theory formulations (cooperative and non-cooperative) were given special attention and a detailed comparison between Shapley value and Nucleolus was provided as approaches for fair cost allocation. To enhance the adaptability of the market and the overall efficiency of the system, we introduce the Transactive Energy Reformulation Model (TE-RM), a hybrid model combining AI-powered congestion pricing with coalition formation and fairness-based incentives. The comparative tables in this paper summarize TEM and TE-RM's strengths and weaknesses and compare it to the centralized and conventional DSM methodologies. Lastly, key research gaps including scalability, regulatory fit, and AI model interpretability are reviewed, and future directions are proposed for the integration of future advanced technologies (e.g., reinforcement learning, blockchain, IoT) to enable stable, fair and interoperable energy markets.
Cahya Kamila Maharani, Relit Nur Edi, Ismail Septayanto Utama
The 4.0 Industrial Revolution has transformed the global economic landscape through the digitalization of financial services, trade, and industrial activities. This transformation has accelerated the growth of the Halal Market, making it one of the fastest-growing economic sectors, driven by the expanding Muslim population, increasing awareness of halal consumption, and rising demand for ethical and sustainable products. In this context, Islamic Fintech has emerged as a strategic innovation that integrates digital financial technologies with the principles of Islamic law and economics. Although studies on Sharia Fintech and the halal industry have grown substantially, research integrating these two domains from the perspectives of Islamic law and Islamic economics remains limited. This study aims to examine the strategic role of Islamic Fintech in strengthening the global Halal Market through an interconnective analytical framework. Employing a qualitative library research approach, the study critically analyzes scholarly literature, regulatory documents, international reports, and previous empirical studies. The findings indicate that Sharia Fintech enhances financial inclusion, transparency, halal traceability, value chain efficiency, and digital governance through the adoption of blockchain, artificial intelligence, smart contracts, and digital payment systems. These innovations contribute to the realization of Maqashid al-Shariah, particularly the protection of wealth (Ḽifáş al-mÄl) and the promotion of public welfare (maᚣlaḼah). The novelty of this study lies in the development of a comprehensive conceptual framework that integrates Islamic law, Islamic economics, digital financial innovation, and Halal Market governance into a unified analytical model.
Rejaul Karim, Md. Mustaqim Roshid, Bablu Kumar Dhar, Abdul Waaje
This study explores the evolving role of green financial technology (Fintech) in sustainability-oriented financial innovation, with a particular focus on climate finance, digital innovation, and environmental governance. Using bibliometric methods, we analyze 72 peer-reviewed publications indexed in Scopus from 2019 to 2024 to map the intellectual structure and emerging trends of green Fintech research. Key technological domains, including blockchain-based carbon markets, AI-powered ESG analytics, and green digital payment systems, are frequently associated in the literature with several Sustainable Development Goals (SDGs), notably SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 8 (Decent Work and Economic Growth). This analysis reveals how digital financial innovations are conceptualized as mechanisms for facilitating access to green capital, strengthening carbon credit ecosystems, and enhancing transparency in climate-aligned investment. However, persistent barriers such as fragmented regulatory frameworks, cybersecurity risks, and digital divides are recurrently identified in the literature as constraints, particularly in emerging economies. Interpreted through Institutional Theory and Stakeholder Theory, the study highlights the importance of coordinated policy innovation, inclusive digital infrastructure, and harmonized ESG standards in shaping the diffusion and governance of green Fintech solutions. By positioning theory as an interpretive lens rather than an empirical test , this research offers a theory-informed, data-driven synthesis that contributes to the growing interdisciplinary discourse on digital finance as a potential enabler of low-carbon, inclusive, and resilient sustainability transitions.
Ovaj rad analizira transformativnu ulogu kriptovaluta u infrastrukturi savremenog organizovanog kriminala, argumentujuÄi da blockchain tehnologija nije samo novi alat za stare kriminalne prakse, veÄ da konstituiĹĄe kvalitativno novu kriminalnu ekonomsku arhitekturu koja mijenja temeljne odnose izmeÄu kriminalnih aktera, Ĺžrtava i institucija. Kroz sistematsku analizu tehniÄkih mehanizama od Bitcoin pseudoanonimnosti i privacy coins, do DeFi protokola i cross-chain hopping tehnika, rad mapira evoluciju kriptovalutnog pranja novca od primitivnih jednokratnih transakcija prema sofisticiranim, viĹĄeslojnim operacijama koje kombinuju tehnoloĹĄku sofisticiranost s institucionalnim ranjivostima globalnog regulatornog mozaika. Posebna analitiÄka paĹžnja posveÄena je sluÄajevima koji demonstriraju konvergenciju kriptokriminala s drĹžavnom strategijom, tj. ransomware koji funkcioniĹĄu kao paraziti na globalnoj digitalnoj ekonomiji, DeFi eksploatacijama koje u minutama dreniraju stotine miliona dolara, i sjevernokorejskim drĹžavno-sponzorisanim hakerskim operacijama koje finansiraju zabranjene oruĹžane programe pod sankcijama. Rad evaluira regulatorne odgovore poput MiCA, FATF Travel Rule i OFAC sankcije, te identifikuje sistemske praznine koje ostavljaju DeFi i peer-to-peer sistem izvan efektivne regulatorne kontrole. ZakljuÄak poziva na fundamentalnu promjenu paradigme regulatornog pristupa, i to od retrospektivne forenzike prema prospektivnoj arhitekturi transparentnosti koja mora biti ugraÄena u same protokole.
Multi-cloud computing is becoming a prominent paradigm to improve scalability, flexibility, reliability and costeffectiveness by leveraging services from multiple cloud providers. But distributed resource management with strong security is a big challenge in multi-cloud scenarios, which are heterogeneous and dynamic. This review paper provides an all inclusive overview on various multi-cloud architectures, deployment models,resource allocation techniques, optimization methods, and security assurance mechanisms. It covers the major resource allocation strategies such as provisioning, scheduling, load balancing, resource scaling and intelligent optimization through machine learning and metaheuristicalgorithms to optimize resource utilization and Quality of Service (QoS). Additionally, the article delves into significant security methods for protecting decentralized cloud systems, including authentication, authorization, encryption, intrusion detection, trust management, and zero-trust designs. Also, through the comparison of the most recent literature, the current research trends, challenges and limitations for optimizing resources while keeping security in mind are pointed out. According to the review, combining AI-powered optimisation with sophisticated security frameworks has the potential to enhance the performance, resilience and reliability of multi-cloud environments. Last but not least, the paper outlines future research avenues for explainable AI, federated learning, blockchain-based trust management, energy-efficient resource allocation, and autonomous cloud orchestration to enable secure, scalable, and sustainable next-generation multi cloud computing environments.
With the evolution of wellness tourism in the digital era, there has been an exponential change in the landscape of travel wellness and preventive health care. Today, the travelers are driven to seek holistic well-being, self-care, and transformative experiences beyond traditional leisure. This growing demand has led to the integration of advanced wellness and tourism technologies, such as artificial intelligence (AI), wearable devices, virtual reality (VR), telemedicine, and blockchain. These innovations enhance personalization, operational efficiency, and accessibility for the customer; they also redesign the delivery and consumption of wellness experiences. As there is a technological shift in the wellness tourism industry, critical challenges arise related to data privacy, the digital divide, sustainability, cultural sensitivity, and the erosion of authenticity in wellness practices. This chapter critically examines the relationship between wellness tourism and emerging technologies. It hides the opportunities and the underlying challenges associated with this transformation. Insights complemented by semi-structured interviews with industry experts and extensive academic literature reviews published between 2015 and 2025 offered a comprehensive exploration of future trends, challenges, and pathways for sustainable development in wellness tourism. It also proposes the framework for ethical technology integration, ensuring the wellness tourism ecosystem remains inclusive and resilient. Inform the ground of the principle of sustainability.
In the last few years, the Internet of Things (IoT) has grown significantly due to technological advancements. However, until recently, there has been no universal set of rules applicable to IoT security. This has opened an area for researchers. The IoT environment enables various smart devices to connect and exchange information; thus, ensuring the authenticity of devices in the IoT network is crucial. We have classified the diverse methods used to authenticate IoT devices to access the data they generate. This study conducted a systematic literature review to identify research gaps, recurring patterns, and potential future directions in IoT authentication, with particular attention to the architectures employed. This review analyzed different authentication techniques and presented their advantages and disadvantages using several criteria for categorization. This survey provides researchers and practitioners with a consolidated understanding of the current state of authentication mechanisms in the IoT. Furthermore, the survey examines emerging authentication paradigms, including blockchain-enabled authentication frameworks, machine-learning-augmented authentication models, and lightweight authentication schemes tailored for resource-constrained IoT devices. The goal of this survey is to aid in creating more robust and secure authentication solutions for the developing IoT by highlighting strengths, limitations, and emerging trends.
User Authentication and Security Systems
Advanced Authentication Protocols Security
Physical Unclonable Functions (PUFs) and Hardware Security
Case Report Forms (CRFs) are essential tools in clinical trials, serving as the primary mechanism for systematic and standardized patient data collection. This chapter discusses the critical role of CRFs in maintaining data integrity, supporting regulatory compliance, and ensuring the accuracy and consistency of clinical trial results. The chapter provides an in-depth exploration of the key principles involved in designing CRFs, including user-centric design, data standardization, and error management. It contrasts the features of well-designed and poorly designed CRFs, highlighting the significant impact that effective CRF design has on clinical trial outcomes. Additionally, the chapter addresses the evolution of CRFs, particularly the transition from paper-based systems to electronic Case Report Forms (eCRFs), and their benefits, including real-time data validation, enhanced accessibility, and compliance with regulatory guidelines. The impact of technological advances such as artificial intelligence, blockchain, and decentralized trials on the future of CRF processes is also discussed. Finally, a sample CRF is presented, providing a practical example of a well-designed form for clinical data collection in a controlled study.
This chapter examines the evolving architecture of digital remittances and diaspora finance in Africa, situating these flows within the broader framework of continental economic integration under the African Continental Free Trade Area (AfCFTA). With remittance inflows to Africa exceeding $96 billion in 2024, the chapter analyses how digital transfer technologies, blockchain-based platforms, and mobile money innovations are reshaping the cost structure, speed, and transparency of cross-border payments. It evaluates the persistent challenge of high transaction costs in Sub-Saharan African corridors and the role of FinTech disruptors in narrowing the gap toward the Sustainable Development Goal target of 3%. The chapter further explores diaspora investment channels, including diaspora bonds and equity platforms, and assesses their potential for productive capital mobilisation aligned with AfCFTA investment priorities. The chapter concludes with recommendations for integrating diaspora finance into continental development strategies.
Medical tourism, often branded as health tourism, involves people traveling beyond regional limits to get advanced healthcare treatments, which is generally determined based on medical payments, availability of specialized treatment, in addition to obtainability of innovative technical support. The implementation of digital advancements such as telemedicine, health informatics, artificial intelligence (AI), and blockchain technology has resulted in a dramatic shift in the health sector. The technological innovations are transforming healthcare delivery, thereby encouraging rural women entrepreneurs to play a significant part in a nationâs health service milieu. To improve service delivery and outreach, women entrepreneurs are using digital platforms such as AI-based diagnostic tools, blockchain for data confidentiality and authenticity, and e-marketing technologies. The study focuses on how women-led businesses are establishing themselves as important facilitators, filling the disparity between overseas clients and healthcare professionals. The observations evaluate the socioeconomic implications of digital adoption, specifically in terms of employment generation, incorporating gender equality, and improved health care accessibility in less developed rural areas, using a blended research approach that combines descriptive and empirical study observations and findings. The most significant challenges and potential advantages confronting rural women in this growing industry are thoroughly investigated, and practical solutions for promoting the sustainability and scalability of such firms are identified. The chapter also highlights rural women entrepreneursâ contributions to improving Indiaâs more equitable, technologically equipped, and globally successful health care travel environment.
Abstract This study explores the role of Artificial Intelligence (AI) in transforming agricultural supply chain management in Bangladesh through a systematic comparative analysis of existing literature, institutional reports, and global case studies. AI technologies including predictive analytics, machine learning, blockchain, and precision agriculture are examined for their potential to address longstanding inefficiencies in Bangladeshâs agri-supply chain. The study finds that AI-driven demand forecasting models using LSTM and ARIMA achieved 89â92% crop yield prediction accuracy, representing a 37% improvement over traditional methods. Smart warehousing systems reduced operational costs by 25% and increased order processing speed by 40%, while blockchain integration cut payment cycles from 15 days to 2.3 days and increased smallholder farmer incomes by 22â25%. Precision agriculture technologies achieved 25% yield growth with 15â20% water savings and 30% fertilizer efficiency gains. Despite these promising outcomes, Bangladeshâs AI adoption rate remains at only 18%, significantly behind India (35%) and Vietnam (28%), primarily due to insufficient infrastructure, lack of digital literacy, and high implementation costs. The study proposes targeted policy interventions including IoT subsidies, farmer training programs, and public-private partnerships to enable inclusive and sustainable AI integration across Bangladeshâs agricultural sector.
Mingqian Li, Rong Du, Andrew BurtonâJones, Jianing Xie
Purpose Grounded in signaling theory, this study examines whether traceability information displaces or complements incumbent quality cues and contrasts the relative efficacy of blockchain-enabled traceability technologies with traditional systems. Design/methodology/approach This study analyzes 18 months of product-level sales data from a global e-commerce platform using a staggered difference-in-differences design with robustness checks. We apply latent Dirichlet allocation topic modeling to consumer reviews and use a synthetic difference-in-differences approach to examine shifts in consumer attention after traceability implementation. Findings Traceability information increases product sales, particularly for lower-reputation brands and diminishes the effect of electronic word-of-mouth, suggesting that diagnostic quality signals matter more than social information signals. Although blockchain-enabled traceability should enhance signal credibility, its observed impact falls short of expectations. Research limitations/implications The sample is limited to the automotive engine oil context in China. Future research should examine other categories and national contexts. Practical implications Platform managers and emerging brands can deploy low-cost traceability labels to boost demand. Blockchain solutions may require consumer education to justify higher implementation costs. Social implications Augmenting supply-chain transparency and product traceability curbs counterfeit and substandard goods, improves consumer welfare, and supports regulatory and sustainability objectives. Originality/value This study systematically assesses the substitutive and complementary roles of traceability signals in a multi-cue setting, tempers optimism about blockchain-enabled traceability and extends research on digital supply-chain transparency and signaling theory.
While much has been written about the volatility of digital assets, academic scholarship has largely overlooked how blockchain technologies have been adopted and reimagined by LGBTQ+ communities. This article addresses that gap through a digital ethnography of queer NFT communities active during the crypto craze of 2022, combining online participant observation with semi-structured interviews. Drawing on JosĂŠ Esteban MuĂąozâs concept of queer futurity, it examines how queer users imagined blockchain as a speculative platform for alternative economic and social possibilityâdespite the financial risks embedded in the technologyâs libertarian and capitalist structures. The article interrogates the utopian rhetoric of inclusion, decentralisation, and wealth redistribution that was deployed within these communities to justify their interest in and holdings of non-fungible tokens (NFTs) and cryptocurrency. Queer leaders leveraged the blockchain to foster inclusive digital communities and promote wealth circulation amongst LGBTQ+ individuals, while community members embraced the technology as a risky opportunity for queer economic mobility. The article positions blockchain as a contested site where competing futurities collideâoffering the illusion of liberation and the reproduction of existing inequalities. It argues that while queer users sought to make the blockchain âqueer from the start,â their efforts were ultimately constrained by the capitalist logics that underpin the technology.
Muhammad Farooq Shaikh, S. Hamza Hassan, Jawwad Shamsi, Alessia Maccaro ¡ 5 authors
Background and objective The integration of blockchain and digital twin (DT) technologies is increasingly recognised as a promising approach for improving healthcare data integrity, interoperability, privacy, and clinical decision support. While digital twins enable dynamic patient modelling and predictive healthcare applications, blockchain provides secure data governance through decentralised trust, auditability, and access control. However, existing research remains fragmented, with limited synthesis of the architectural integration, regulatory readiness, ethical governance, and interoperability of blockchain-enabled healthcare digital twin systems. This systematic scoping review addresses these gaps by providing a comprehensive architectural and compliance-oriented analysis of the current evidence. Methods A systematic scoping review was conducted following PRISMA 2020 guidelines using Scopus, PubMed, and Web of Science. From 148 identified records, 55 eligible studies published between 2020 and 2025 were included after duplicate removal and eligibility screening. Data were extracted on digital twin functionality, blockchain architecture, healthcare application domains, consensus mechanisms, privacy-preserving strategies, and regulatory and ethical alignment. Structured Python-based visual mapping and comparative analyses were performed to identify architectural, governance, and compliance patterns across the literature. Results The findings demonstrate that blockchain is predominantly employed to provide access control, audit logging, data integrity, consent management, and secure data provenance within healthcare digital twin ecosystems. Patient-level and EHR-centred digital twins represented the most mature application areas, whereas cross-domain and infrastructure-level frameworks dominated early architectural exploration. The review identifies recurring compliance-oriented architectural patterns while revealing substantial gaps in clinically validated deployments, interoperability with established healthcare standards, decentralised governance models, and formal implementation of GDPR- and HIPAA-compliant engineering practices. Comparative heatmap analyses further highlight the uneven maturity of ethical governance and regulatory integration across blockchain functionalities. Conclusion This review provides the first comprehensive compliance-oriented architectural synthesis of blockchain-enabled healthcare digital twin systems by integrating technical architecture, regulatory readiness, ethical governance, and privacy-preserving design patterns within a unified analytical framework. The proposed architectural mapping identifies critical research gaps in interoperability, governance engineering, consensus optimisation, and real-world clinical validation, providing a foundation for the development of trustworthy, GDPR/HIPAA-aligned, FHIR-compatible, and clinically interoperable healthcare digital twin ecosystems.
K. Satheshkumar, S. Ramalingam, A. Suresh Babu, S. Murugesan
ABSTRACT Vehicular ad hoc networks (VANETs) are essential components of intelligent transportation systems that facilitate realâtime communication between vehicles (V2V) and between vehicles and infrastructure (V2I). Despite their importance, VANETs face challenges, such as high node mobility, energy limitations, security risks, and everâchanging network topologies. Existing clustering and routing algorithms often struggle to manage the instability caused by mobility, energy disparities, and secure congestionâfree communication simultaneously. To address these challenges, this work introduced an integrated crossâlayer framework featuring three innovative algorithms: mobilityâaware black hole clustering (MâBHC), energyâaware piranha optimization algorithm (EPOA), and crossâlayer multiâattribute blockchain routing with congestion control (CLâMABRC). The MâBHC algorithm enhances the stability of clusters and counters blackâhole attacks by forming clusters dynamically based on realâtime vehicle mobility patterns. EPOA optimizes the selection of cluster heads (CHs) by reducing energy consumption through a bioâinspired resource allocation strategy modeled on piranha predation behavior. CLâMABRC addresses network congestion and security using blockchainâbased verification and crossâlayer routing decisions informed by multiâattribute metrics. Extensive simulations were conducted with a setting of 100 veh/km 2 . The proposed framework showed significant performance improvements over benchmark protocols, such as optimal securityâaware clusterâbased hybrid geographical and opportunistic routing (OSCâGOR), enhanced locationâaided ant colony routing (ELAACR), trustâbased multiâobjective honey badger algorithm (TMOHBA), and robust cryptographic scheme for reliable data communication (RCSRC). It achieved a throughput of 99.89 Kbps, endâtoâend delay of 3.9 ms, collision rate of 21.8%, energy consumption of 41.98%, and jitter of 0.05 ms. Together, the MâBHC, EPOA, and CLâMABRC algorithms create a robust, energyâefficient, and secure communication framework for VANETs, enhancing scalability, reliability, and realâtime performance in transportation systems.
The use of a wireless sensor network is increasingly supporting e-governance functions such as municipal utility monitoring, environmental monitoring, grievance-based field reporting, and smart public service delivery. Most wireless sensor network architectures rely on a gateway or database. However, this introduces vulnerabilities to data integrity, node accountability, and auditability. This study examines transparency through a blockchain-enabled WSN architecture for e-governance. The study applies a reproducible Python-based Monte Carlo simulation with a fixed random seed, five node densities, three architectural scenarios, and 450 observations. The scenarios that are compared in this work are a normal WSN, a centralized secure WSN, and a permissioned blockchain-enabled WSN with smart-contract-based identity registration, hash-linked data records, trust scoring, and tamper verification. Descriptive statistics, one-way ANOVA, Welch t-tests, Pearson correlation, and multiple linear regression analysis. The blockchain-assisted WSN, as evidenced by the simulation findings of our project, produced the highest mean data integrity score, tampering detection rate, trust score, malicious node detection rate, and packet delivery ratio. The architecture also improved the composite service efficiency index relative to the conventional baseline, even though it introduced higher latency, transaction confirmation time, and energy consumption. The research indicates that the permissioned blockchain can enhance public-sector WSN transparency with edge aggregation and lightweight cryptographic operations along with carefully tuned endorsement rules. The methods presented in this study allow for scrutiny of secure WSN designs tailored for e-governance.
The development of blockchain technology has given rise to the Decentralized Autonomous Organization (DAO), a new business organizational model that operates through smart contracts in a decentralized manner, without a conventional management structure. The existence of DAOs has not been accommodated in the Indonesian corporate legal system, creating a legal vacuum regarding legal subject status, accountability, legal standing, taxation, and dispute resolution. This study aims to analyze the characteristics of DAOs from a corporate law perspective and the urgency of convergence between corporate law and blockchain technology in its regulation in Indonesia. The study employs a normative juridical method with statutory, conceptual, and comparative approaches. The results indicate the need for regulations that recognize and regulate DAOs as digital business entities to achieve legal certainty, legal protection, and a sustainable digital investment climate.
B Santhosh Kumar, P. Penchala Prasad, M. Raghavendra Reddy
Abstract Alzheimerâs disease is a neurodegenerative disorder that affects millions of individuals worldwide, making early diagnosis through Magnetic Resonance Imaging a significant clinical necessity. Existing medical image analysis techniques often suffer from limitations associated with inadequate preprocessing, reduced sensitivity to subtle abnormalities in the hippocampus and cortex, poor generalization across heterogeneous MRI acquisition systems, and insufficient mechanisms for secure medical data management. To address these challenges, this research proposes an integrated framework combining the Internet of Medical Things (IoMT), Artificial Intelligence, and blockchain technology for secure and efficient Alzheimerâs disease monitoring. The proposed framework employs Feature Pooling VGG16 (FPVGG16) for discriminative feature extraction, while feature selection is optimized using the Wave Search Binary Waterwheel Plant Optimization algorithm. Subsequently, a feature-selective Coordinated Xception-based Convolutional Spatial Network (CXCSN) is utilized for accurate disease classification. Blockchain technology is incorporated to provide secure, tamper-resistant, and privacy-preserving management of patient information and MRI records. Experimental evaluations conducted on the Alzheimerâs Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets validate the effectiveness of the proposed framework, achieving accuracies of 99.31% and 99.21%, precisions of 99.28% and 99.25%, and recalls of 99.18% and 99.14 %, respectively. The results indicate that the proposed framework provides an effective solution for secure, reliable, and highly accurate Alzheimerâs disease diagnosis and monitoring.
Purpose This study aims to examine the feasibility of blockchain adoption during investment banksâ Know Your Customer (KYC) validation processes. It studies the role played by government in regulating the blockchain-based KYC process. Design/methodology/approach A framework based on the extended technology acceptance model (TAM) was conceptualised to formulate six hypotheses. Based on this, a structured questionnaire was developed and administered among the employees of investment banks through a multi-stage sampling technique. The final sample, comprising 605 responses, was analysed using a covariance-based structural equation modelling (Mediation Analysis) on JASP V.19. Findings The present research explains that the government, as a mediating variable, has a 45.7% direct impact and 54.3% indirect effect on investment banks in the adoption and actual usage of blockchain technology for KYC validation. The perceived ease of use, perceived usefulness and attitude to use technology are key factors that influence its adoption for front-office operations. Perceived ease of use is a dominant indicator within the model. Research limitations/implications This study contributes theoretically by extending the existing TAM model with its practical application in the KYC process during validation of customer documentation in the banking industry, adding practical relevance to the regulatory framework. Originality/value The research derives its originality from the mediating role of government regulation in implementing KYC through blockchain. It proposes a blueprint of a working model that can be internalised to optimise the processes, extending the existing theory and its application with practical relevance.
The rapid advancement of artificial intelligence (AI) and blockchain technologies has fundamentally transformed the normative foundations, authority structures, and legitimacy of contemporary legal systems. While these technologies are commonly portrayed as instruments for enhancing efficiency and legal certainty, their increasing integration into legal decision-making raises profound philosophical questions concerning the nature of law, justice, and human agency. This article critically examines how AI and blockchain reshape legal normativity through the lens of legal philosophy. Employing a normative juridical methodology supported by conceptual and philosophical approaches, the study analyzes the implications of algorithmic decision-making and decentralized technological infrastructures for the evolution of legal authority. The findings demonstrate a paradigmatic shift from human-centered normative reasoning toward computational rationality grounded in algorithmic logic. AI replaces interpretative legal reasoning with probabilistic prediction, privileging statistical inference over moral deliberation. Simultaneously, blockchain institutionalizes automated legal enforcement through smart contracts, thereby minimizing interpretative discretion and limiting the contextual flexibility traditionally required to achieve substantive justice. These developments contribute to the emergence of what this article conceptualizes as post-human legal normativity, in which legal authority increasingly resides within technological systems rather than human reasoning and institutional judgment. The study argues that this transformation generates significant challenges to justice, transparency, accountability, and democratic legitimacy. The growing reliance on algorithmic authority risks reducing law to a technical mechanism detached from its ethical and normative foundations. Consequently, the philosophy of law must be reconstructed to reaffirm the centrality of human agency in legal governance and to ensure that emerging technologies function as instruments serving legal values rather than autonomous sources of legal authority.
Transformer-based detectors for Solidity smart contracts almost universally encode a contract within a single 512-token window, then attribute performance differences to the choice of pre-trained encoder. We show this attribution is misplaced. On DIVE-25 (22,330 deployed contracts, eight DASP categories, multi-label at 2.46 labels per contract) the median contract occupies 2,994 sub-word tokens and only 5.48% fit a single window. We segment each contract at top-level declaration boundaries, pack the segments greedily into at most 24 chunks of 510 tokens for an effective context of 12,240 tokens covering 98.25% of the corpus, and recombine the chunk representations with a bidirectional LSTM under additive attention. Holding preprocessing, chunk budget, pooling, aggregator, loss, schedule, seeds and split identical, the extended context is worth +0.1038 micro-F1 and +0.1722 macro-F1 over single-window truncation, roughly four times the benefit of the best available encoder. The loss under truncation is markedly uneven: Front Running falls by 0.294 and Time manipulation by 0.262, while Access Control, whose indicators sit near the top of a file, loses 0.010. Fifty-one structural measurements and a five-relation contract graph enter the classifier through per-class gates initialised at Ď(â4) â 0.018, so any contribution must be learned; both open, and the resulting gain is 1.9 times larger on categories below 900 test instances. Under family-aware leakage-controlled partitioning the complete system reaches 0.8435 micro-F1 and0.7775 macro-F1, with the fusion gain significant under a paired bootstrap (macro-F1 +0.0173, 95% CI [+0.0113, +0.0236]). We report every result additionally on a twin-free test subset from which the 39.58% of test contracts sharing a structural twin with training are removed. Finally, evaluated against human-verified exploitability judgements the detector scores 0.455 mean AUC, below a baseline built from contract size and compiler version alone (0.735), bounding what any detector trained on analyser consensus can be claimed to do.
This chapter examines the transformative role of blockchain technology, artificial intelligence (AI), and smart contracts in reshaping trade finance and customs modernisation across Africa, with particular emphasis on the African Continental Free Trade Area (AfCFTA) framework. It explores how distributed ledger technologies are enhancing transparency and reducing transaction costs in cross-border trade, while AI-driven credit scoring and risk assessment models are expanding financial inclusion for underserved enterprises. The chapter analyses the deployment of smart contracts for automating trade documentation and compliance processes, and evaluates the impact of these technologies on fraud reduction and supply chain traceability. Drawing on real-world cases from the Pan-African Payment and Settlement System (PAPSS), Flutterwave, Kifiya, and the AfCFTA Digital Trade Protocol, the chapter highlights both opportunities and governance challenges, including data privacy, regulatory fragmentation, scalability constraints, and the digital infrastructure divide that characterises much of the continent. Policy recommendations for harmonised regulatory frameworks and capacity building are advanced.
Law, logistics, and international trade
Legal, Health, Environmental and COVID-19 Challenges
Land ownership management is a critical administrative process that requires secure record maintenance, transparent ownership verification, and efficient property transfer mechanisms. Conventional land registry systems primarily depend on centralized databases and paper-based documentation, making them susceptible to document forgery, unauthorized modifications, duplicate ownership claims, lengthy verification procedures, and administrative inefficiencies. These limitations often result in ownership disputes, reduced public trust, and delays in property transactions. This paper presents a Blockchain-Enabled Secure Land Registry Framework that leverages blockchain technology to establish a decentralized, transparent, and tamper-resistant platform for land registration and ownership management. The proposed system integrates a React.js-based user interface with a Node.js and Express.js backend, while Firebase Authentication and Firebase Firestore manage user authentication, supporting documents, and application data. Ethereum smart contracts developed using Solidity are employed to securely record land registration, government verification, and ownership transfer transactions on the blockchain, with Ganache serving as the blockchain testing environment. Every approved transaction generates a unique blockchain transaction hash, enabling secure verification, complete traceability, and immutable ownership history. The hybrid architecture combines the scalability of cloud-based data management with the integrity of blockchain technology to ensure efficient record retrieval while preventing unauthorized alterations. The implemented framework demonstrates secure land registration, transparent ownership transfer, simplified government verification, and reliable auditability with minimal operational complexity. The proposed solution provides a scalable and cost-effective approach for modern digital land administration and establishes a strong foundation for future integration with national land registries, electronic identity verification, GIS-based property mapping, and mobile-enabled citizen services.