In this chapter we provide an overview of the concept of blockchain technology and its potential to disrupt the world of banking through facilitating global money remittance, smart contracts, automated banking ledgers and digital assets. In this regard, we first provide a brief overview of the core aspects of this technology, as well as the second-generation contract-based developments. From there we discuss key issues that must be considered in developing such ledger based technologies in a banking context.
Steve Huckle, Rituparna Bhattacharya, Martin White
et al.
This paper explores how the Internet of Things and blockchain technology can benefit shared economy applications. The focus of this research is understanding how blockchain can be exploited to create decentralised, shared economy applications that allow people to monetise, securely, their things to create more wealth. Shared economy applications such as Airbnb and Uber are well-known applications, but there are many other opportunities to share in the digital economy. With the recent interest in the Internet of Things and blockchain, the opportunity exists to create a myriad of sharing applications, e.g. peer-to-peer automatic payment mechanisms, foreign exchange platforms, digital rights management and cultural heritage to name but a few. While many types of shared economy scenarios are proliferating, few of them, so far, leverage the Internet of Things and blockchain as technologies to build distributed applications. This paper discusses how we might make use of the Internet of Things and blockchains to create secure shared economy distributed applications. Presented are examples of such distributed applications in the context of an Internet of Things architecture using blockchain technology.
BackgroundThe notion of smart city has grown popular over the past few years. It embraces several dimensions depending on the meaning of the word “smart” and benefits from innovative applications of new kinds of information and communications technology to support communal sharing.MethodsBy relying on prior literature, this paper proposes a conceptual framework with three dimensions: (1) human, (2) technology, and (3) organization, and explores a set of fundamental factors that make a city smart from a sharing economy perspective.ResultsUsing this triangle framework, we discuss what emerging blockchain technology may contribute to these factors and how its elements can help smart cities develop sharing services.ConclusionsThis study discusses how blockchain-based sharing services can contribute to smart cities based on a conceptual framework. We hope it can stimulate interest in theory and practice to foster discussions in this area.
Digital technologies such as blockchain, Internet of Things (IoT), and artificial intelligence (AI) are increasingly applied in food supply chains (FSCs) to enhance traceability, monitoring, and quality detection. However, whether these technological advancements ultimately contribute to improved nutritional security remains unclear. This scoping review systematically examined the application of digital technologies across food supply chains and assessed their impacts on food safety, food loss reduction, and nutritional outcomes. Following PRISMA guidelines, we searched Web of Science, Scopus, and PubMed for empirical studies published between 2015 and 2025, with supplementary searches conducted in the Cochrane Library and Global Health databases to ensure comprehensive coverage of nutrition-related evidence. Ultimately, 46 studies were included for analysis. Results revealed that blockchain (41.3%), IoT (26.1%), and AI/machine learning (19.6%) constitute the primary technological approaches, with storage and transportation being the most concentrated application areas (41.3%). Evidence for positive impacts on food safety and loss reduction is substantial, with 89% and 83% of relevant studies reporting favorable outcomes, respectively. However, only 6.5% of included studies directly measured nutrition-related outcomes, representing a critical evidence gap. This asymmetric evidence distribution suggests that while digital technologies demonstrate clear value in improving supply chain efficiency and food safety, the pathway from technological performance to nutritional improvement remains largely unverified. Future research should incorporate nutrition indicators into evaluation frameworks and prioritize studies in low-income countries where food loss and nutritional insecurity are most severe.
This article examines the evidentiary value of blockchain technology in civil litigation through a comparative legal analysis. While blockchain’s technical features offer significant potential for creating reliable evidence, the study demonstrates that technical security alone does not establish legal certainty. The research analyses how different legal systems approach blockchain evidence, including China’s direct integration into internet courts, the United States’ cautious application within existing electronic evidence frameworks subject to hearsay rules, the European Union’s technology-neutral approach through eIDAS regulations, and the varied national practices in France, Germany, the United Kingdom, and Türkiye. The findings reveal that blockchain records face inherent functional limitations, particularly in proving physical-world events, as they can only guarantee data integrity within the digital environment. The study identifies three scenarios where blockchain evidence proves most effective: proving transactions executed directly on blockchain networks, serving as an electronic detection instrument for transactions occurring outside the network, and recording real-world events directly onto blockchain systems. However, challenges persist across jurisdictions, including the absence of harmonised standards, difficulties in establishing attribution, concerns about the “garbage in, garbage out” principle, and the need for expert testimony in evaluating blockchain evidence. The article concludes that the effective integration of blockchain into evidence law requires clear normative frameworks that balance technical reliability with procedural safeguards. It recommends establishing specific admissibility criteria for blockchain records, developing standardised verification mechanisms, providing judicial training on the technology, and coordinating with international standards such as UNCITRAL and EU regulations to ensure uniformity across jurisdictions.
Afroja Akther, Ayesha Arobee, Abdullah Al Adnan
et al.
As artificial intelligence (AI) systems become increasingly complex and autonomous, concerns over transparency and accountability have intensified. The "black box" problem in AI decision-making limits stakeholders' ability to understand, trust, and verify outcomes, particularly in high-stakes sectors such as healthcare, finance, and autonomous systems. Blockchain technology, with its decentralized, immutable, and transparent characteristics, presents a potential solution to enhance AI transparency and auditability. This paper explores the integration of blockchain with AI to improve decision traceability, data provenance, and model accountability. By leveraging blockchain as an immutable record-keeping system, AI decision-making can become more interpretable, fostering trust among users and regulatory compliance. However, challenges such as scalability, integration complexity, and computational overhead must be addressed to fully realize this synergy. This study discusses existing research, proposes a framework for blockchain-enhanced AI transparency, and highlights practical applications, benefits, and limitations. The findings suggest that blockchain could be a foundational technology for ensuring AI systems remain accountable, ethical, and aligned with regulatory standards.
The convergence of blockchain and metaverse technologies is poised to redefine how Global Value Chains (GVCs) create, capture, and distribute value, yet scholarly insight into their joint impact remains scattered. Addressing this gap, the present study aims to clarify where, how, and under what conditions blockchain-enabled transparency and metaverse-enabled immersion enhance GVC performance. A systematic literature review (SLR), conducted according to PRISMA 2020 guidelines, screened 300 articles from ABI Global, Business Source Premier, and Web of Science records, yielding 65 peer-reviewed articles for in-depth analysis. The corpus was coded thematically and mapped against three theoretical lenses: transaction cost theory, resource-based view, and network/ecosystem perspectives. Key findings reveal the following: 1. digital twins anchored in immersive platforms reduce planning cycles by up to 30% and enable real-time, cross-border supply chain reconfiguration; 2. tokenized assets, micro-transactions, and decentralized finance (DeFi) are spawning new revenue models but simultaneously shift tax triggers and compliance burdens; 3. cross-chain protocols are critical for scalable trust, yet regulatory fragmentation—exemplified by divergent EU, U.S., and APAC rules—creates non-trivial coordination costs; and 4. traditional IB theories require extension to account for digital-capability orchestration, emerging cost centers (licensing, reserve backing, data audits), and metaverse-driven network effects. Based on these insights, this study recommends that managers adopt phased licensing and geo-aware tax engines, embed region-specific compliance flags in smart-contract metadata, and pilot digital-twin initiatives in sandbox-friendly jurisdictions. Policymakers are urged to accelerate work on interoperability and reporting standards to prevent systemic bottlenecks. Finally, researchers should pursue multi-case and longitudinal studies measuring the financial and ESG outcomes of integrated blockchain–metaverse deployments. By synthesizing disparate streams and articulating a forward agenda, this review provides a conceptual bridge for international business scholarship and a practical roadmap for firms navigating the next wave of digital GVC transformation.
Abstract With the advancement of quantum computing and increasing demands for privacy protection in decentralized applications such as blockchain, digital signature schemes face significant challenges in simultaneously achieving anonymity, traceability, and resistance to dictatorship surveillance. Recently, anamorphic signatures were introduced to address extreme censorship scenarios, enabling parties to embed hidden messages within authenticated signatures even when communication channels and keys are entirely controlled by an adversarial dictator. Motivated by this scenario, we propose the first anamorphic group signature scheme based on the MAYO multivariate post-quantum signature algorithm. Our scheme achieves indistinguishable embedding of anamorphic messages into signatures, enabling confidential communication that remains undetectable even under strict monitoring. We further introduce an efficient confirmation and disavowal protocol combining 3-pass and 5-pass MQ identification protocols, facilitating secure member identification without compromising anonymity. Finally, a lightweight signature-opening mechanism based on salted hash bindings ensures that only the group manager can disclose signer identities during disputes. Our construction provides a practical, quantum-resistant, and dictator-resistant cryptographic toolset, making it particularly suitable for consortium blockchains, private chains, and regulated governmental networks.
Nibras Abo Alzahab, Giulia Rafaiani, Massimo Battaglioni
et al.
Blockchain technology, which was introduced for supporting cryptocurrencies, today provides a decentralized infrastructure for general information storage and execution of algorithms, thus enabling the conversion of many applications and services from a centralized and intermediated model to a decentralized and disintermediated one. In this paper we focus on biometric authentication, which is classically performed using centralized systems, and could hence benefit from decentralization. For such a purpose, however, an inherent contradiction between biometric applications and blockchain technology must be overcome, as the former require keeping biometric features private, while blockchain is a public infrastructure. We propose a blockchain-based biometric authentication protocol that enables decentralization and resilience while protecting the privacy, personal data, and, in particular, biometric features of users. The protocol we propose leverages fuzzy commitment schemes to allow biometric authentication to be performed without disclosing biometric data. We also analyze the security of the protocol we propose by considering some relevant attacks.
Faisal Haque Bappy, Tarannum Shaila Zaman, Md Sajidul Islam Sajid
et al.
While blockchains initially gained popularity in the realm of cryptocurrencies, their widespread adoption is expanding beyond conventional applications, driven by the imperative need for enhanced data security. Despite providing a secure network, blockchains come with certain tradeoffs, including high latency, lower throughput, and an increased number of transaction failures. A pivotal issue contributing to these challenges is the improper management of "conflicting transactions", commonly referred to as "contention". When a number of pending transactions within a blockchain collide with each other, this results in a state of contention. This situation worsens network latency, leads to the wastage of system resources, and ultimately contributes to reduced throughput and higher transaction failures. In response to this issue, in this work, we present a novel blockchain scheme that integrates transaction parallelism and an intelligent dependency manager aiming to reduce the occurrence of conflicting transactions within blockchain networks. In terms of effectiveness and efficiency, experimental results show that our scheme not only mitigates the challenges posed by conflicting transactions, but also outperforms both existing parallel and non-parallel Hyperledger Fabric blockchain networks achieving higher transaction success rate, throughput, and latency. The integration of our scheme with Hyperledger Fabric appears to be a promising solution for improving the overall performance and stability of blockchain networks in real-world applications.
Building information modeling (BIM) and blockchain applications have introduced significant benefits to the architecture, engineering, construction, and operation (AECO) industry in recent years. Although publications on BIM and blockchain integration have been increasing, no systematic examination of the present status and managerial implications of integrated BIM and blockchain has been conducted. To bridge this gap, this paper conducts a state-of-the-art review of the development of integrated BIM and blockchain in a built environment. A combination of qualitative and quantitative methods was adopted to synthesize and analyze the research evidence. The results revealed five key managerial implications of BIM integration with blockchain at the project level: design and collaboration, financial management, construction management, information management, and integration management (with other cutting-edge technologies). Challenges and opportunities are outlined and articulated from both technological and managerial perspectives, such as stakeholder management, impact assessment, real-time project management, information redundancy, and incompatibility.
As artificial intelligence (AI) is innovating various industries, there are concerns about the trust and transparency of AI-driven inference and training results. To tackle these issues, decentralized solutions employing blockchain have been proposed, but they often face challenges such as a long execution time of inference or training transactions, inefficient verification, and incompatibility with existing blockchains, especially when dealing with large-scale models. To overcome these limitations, we introduce BRAIN, a Blockchain-based Reliable AI Network. A unique feature of BRAIN is its two-phase transaction execution mechanism, which allows pipelined processing of inference or training transactions. Also, BRAIN performs asynchronous, aggregator-free federated learning, where each training node proposes its local model to the blockchain, computes the next global model incrementally based on the evaluation results of the proposed models, and calculates its local model using the global model and its own data, all asynchronously. For scalable verification of inference and training processes, BRAIN employs a verifiable, randomly selected committee. It reaches a consensus through a smart contract on the inference output or the evaluation score of a proposed model. Finally, BRAIN can work on an existing blockchain and run its inference and training transactions with regular transactions efficiently. Our experimental result with the GPT-J-6B model on an Ethereum-compatible chain shows that BRAIN affects the blockchain throughput gracefully, as the frequency of the inference requests reaches up to that of the most popular blockchain services today, with few timed-out requests and reasonable gas fees. This is in sharp contrast to the result of previous single-phase inference transactions. It is also shown that BRAIN converges well with asynchronous federated learning.
To address the centralized trading demand within industrial parks and the scattered peer-to-peer trading demand outside industrial parks, this paper proposes a blockchain-based joint auction architecture for distributed energy in microgrids inside and outside industrial parks. By combining blockchain technology and auction theory, the architecture integrates the physical energy transactions within industrial parks with the distributed transactions in external microgrids to meet the centralized trading demand within industrial parks and the scattered peer-to-peer trading demand outside industrial parks, optimizing resource allocation and improving system resilience. In the microgrid auction mechanism for industrial parks, considering distributed energy providers (sellers) and distributed energy buyers, an auction mechanism with power transmission distance, average electricity price, and enterprise nature as its main attributes was constructed to maximize social welfare, realizing efficient energy flow in a multi-microgrid environment and enabling coordinated mutual benefits for producers and consumers within the region. Finally, a case study was conducted on the joint auction mechanism for microgrids inside and outside industrial parks, including the impacts of market dynamics and user preferences on electricity prices using different trading methods, the computational results using different trading matching methods (comparing single-attribute and multi-attribute methods), and multi-dimensional verification of user satisfaction with peer-to-peer transactions in a blockchain environment. The effectiveness of the joint trading between physical energy transactions within industrial parks and external microgrids was demonstrated, which could efficiently coordinate energy allocation inside and outside the parks and reduce the cost of energy configuration.
Abstract The network layer plays a crucial role in blockchain systems, enabling essential functions such as message broadcasting and data synchronization. Enhancing data transmission structures and methods at this layer is key to improving scalability and addressing performance limitations. Currently, the uneven distribution of neighboring node lists and the lack of awareness of underlying linkages in coverage networks hinder the efficiency and comprehensiveness of information transmission. To tackle these challenges, this study introduces a dual-layer transmission model, FPSblo-EP, which divides the blockchain P2P network into two layers: the regular node layer and the tagged node layer. In the initial stage, network nodes are treated as points in a point cloud, and farthest point sampling is applied to the P2P network nodes. During this process, geographic distances between nodes serve as input parameters, while node degrees are used as point weights. Tagged nodes can then provide efficient and stable inter-group routing for regular nodes, creating a hierarchical transmission architecture. This model improves both transmission performance and scalability in blockchain overlay networks. Experimental results show that FPSblo-EP reduces message coverage latency by 22%, redundancy by 26%, and the network stretch coefficient by 28%, demonstrating superior load-balancing capabilities and enhanced network reliability.
Moustafa Mowaffak Saad, Dalia Sobhy, Amani A. Saad
Blockchainsand smart contracts are pivotal in transforming interactions between systems and individuals, offering secure, immutable, and transparent trust-building mechanisms without central oversight. However, Smart Contracts face limitations due to their reliance on blockchain-contained data, a gap addressed by ’Oracles’. These bridges to external data sources introduce the ’Oracle problem’, where maintaining blockchain-like security and transparency becomes vital to prevent data integrity issues. This paper presents <i>Veritas</i>, a novel decentralized oracle system leveraging a layer-2 scaling solution, enhancing smart contracts’ efficiency and security on Ethereum blockchains. The proposed architecture, explored through simulation and experimental analyses, significantly reduces operational costs while maintaining robust security protocols. An innovative node selection process is also introduced to minimize the risk of malicious data entry, thereby reinforcing network security. <i>Veritas</i> offers a solution to the Oracle problem by aligning with blockchain principles of security and transparency, and demonstrates advancements in reducing operational costs and bolstering network integrity. While the study provides a promising direction, it also highlights potential areas for further exploration in blockchain technology and oracle system optimization.