The healthcare sector increasingly explores Distributed Ledger Technology (DLT) and Health Web 3.0 Decentralized Applications (DApps) as promising solutions for patient-centric data management, data sovereignty, and privacy-preserving systems. Despite significant research at the intersection of blockchain and healthcare, current efforts predominantly address isolated technical challenges—focusing narrowly on specific mechanisms such as confidentiality, privacy, or individual smart contract vulnerabilities. Even cybersecurity assessments typically examine discrete attack vectors rather than comprehensive threat landscapes. This fragmented approach limits our ability to build trustworthy systems and delays real-world adoption, as stakeholders lack frameworks to holistically evaluate security posture. This study addresses this gap by conducting a comprehensive threat modeling analysis of Health Web 3.0 DApps, taking into account the complex and interconnected security challenges inherent in blockchain-based healthcare systems. We employ a multi-framework approach integrating LINDDUN threat modeling methodology, OWASP Top 10 Smart Contract Vulnerabilities catalog, and Threat Dragon analytical tool to systematically identify, categorize, and evaluate security risks across the entire application stack. Our analysis maps threats spanning smart contract design flaws, cross-chain interaction vulnerabilities, decentralized identity management weaknesses, unauthorized data access risks, and denial-of-service attack vectors. The primary contribution of this work is demonstrating the critical importance and practical value of holistic threat modeling in blockchain healthcare systems. Our findings reveal interdependencies between seemingly isolated vulnerabilities and show how comprehensive security assessment enhances data privacy protection, smart contract integrity, and overall application resilience. This research provides stakeholders with a systematic methodology for deriving trust in blockchain healthcare solutions, advancing both regulatory compliance and user confidence in decentralized medical data management systems.
No trade theorems examine conditions under which agents cannot agree to disagree on the value of a security which pays according to some state of nature, thus preventing any mutual agreement to trade. A large literature has examined conditions which imply no trade, such as relaxing the common prior and common knowledge assumptions, as well as allowing for agents who are boundedly rational or ambiguity averse. We contribute to this literature by examining conditions on the private information of agents that reveals, or verifies, the true value of the security. We argue that these conditions can offer insights in three different settings: insider trading, the connection of low liquidity in markets with no trade, and trading using public blockchains and oracles.
The paper explores the use of Deep Reinforcement Learning (DRL) in stock market trading, focusing on two algorithms: Double Deep Q-Network (DDQN) and Proximal Policy Optimization (PPO) and compares them with Buy and Hold benchmark. It evaluates these algorithms across three currency pairs, the S&P 500 index and Bitcoin, on the daily data in the period of 2019-2023. The results demonstrate DRL's effectiveness in trading and its ability to manage risk by strategically avoiding trades in unfavorable conditions, providing a substantial edge over classical approaches, based on supervised learning in terms of risk-adjusted returns.
Abstract The Bangladesh Readymade Garments (RMG) industry faces increasing pressure to enhance sustainability and transparency across its complex supply chain. This research develops a blockchain-based Green Supply Chain Management (GSCM) framework to address these challenges. Through a structured review of existing literature, the study identifies key sustainability challenges in GSCM and explores how blockchain can help overcome these challenges, thereby providing a foundation for developing a blockchain-based GSCM framework. The proposed framework facilitates the end-to-end monitoring of sustainability practices, from the procurement of raw materials to the production of finished garments, by utilizing the immutability and transparency of blockchain technology. Smart contracts enforce predefined sustainability criteria, ensuring stakeholder accountability while providing real-time data to drive continuous improvements in resource efficiency and overall sustainability performance. This research addresses a critical gap in the existing literature by proposing a context-specific framework that integrates transparency and sustainability functionalities within a blockchain-based GSCM system. The framework aligns with relevant Sustainable Development Goals (SDGs) and offering a novel approach to achieving a more transparent, accountable, and sustainable future for the Bangladesh RMG industry.
The integration of blockchain technology within the domain of digital cultural heritage resources (DCHR) has emerged as a pivotal approach over the past decade, offering a secure and transparent platform for documentation, ownership transfer, and verification. This paper investigates the current challenges in managing DCHR and analyzes the corresponding solutions. We discuss outstanding technical implementations such as the “Digital Dunhuang Open Material Library” and “Salsal.” Our study identifies emerging blockchain trends in cultural heritage preservation and proposes future research directions. Through an analytical examination of distributed consensus mechanisms and blockchain deployment scenarios, this study proposes methodological pathways for implementing the DCHR management framework. We call for continued optimization of consensus protocols, expansion of blockchain application scenarios, and establishment of supportive policies to bridge the gap between decentralized innovation and institutional compliance requirements.
Abdullah Ayub Khan, Asif Ali Laghari, Roobaea Alroobaea, Abdullah M. Baqasah · 7 authors
The Internet of Things (IoMT) has revolutionized the global landscape by enabling the hierarchy of interconnectivity between medical devices, sensors, and healthcare applications. Significant limitations in terms of scalability, privacy, and security are associated with this connection. This study presents a scalable, lightweight hybrid authentication system that integrates blockchain and edge computing within a Hyperledger Consortium network to address such real-time problems, particularly the use of Hyperledger Indy. For secure authentication, Hyperledger ensures a permissioned, decentralized, and impenetrable environment, while edge computing lowers latency by processing data closer to IoMT devices. The proposed framework balances security and computing performance by utilizing a hybrid cryptographic technique, like NuCypher Threshold Proxy Re-Encryption. Applicational activities are now appropriate for IoMT devices with limited resources thanks to this integration. By facilitating cooperation between numerous stakeholders with restricted access, the consortium network improves scalability and data governance. Comparing the proposed framework to the state-of-the-art techniques, experimental evaluation shows that it reduces latency by 2.93% and increases authentication efficiency by 98.33%. Therefore, in contrast to current solutions, guarantee data integrity and transparency between patients, consultants, and hospitals. The development of dependable, scalable, and secure IoMT applications is facilitated by this work, enabling next-generation medical applications.
Zsofia Baruwa, Sanjay Bhattacherjee, Sahil Rey Chandnani, Zhen Zhu
This work is the first study on the perceptions of social media users about cryptocurrency attacks. The double-spending or 51% attack being the most fundamental attack on cryptocurrencies, it is the focus of this study. As a first step, we create a first-of-its-kind comprehensive list of 31 events of 51% attacks on various proof-of-work cryptocurrencies, showing that these events are quite common. This list contradicts the general perception about the security of cryptocurrencies, particularly portrayed in the Executive Order establishing a Strategic Bitcoin Reserve and a Digital Asset Stockpile in the US. We design the methodologies for our new study of user perceptions around these attacks. We create datasets containing tweets from the time of the attack events, and compare them with benchmark data from normal times. We define parameters for profiling these datasets based on user perceptions – sentiments and emotions. We study the variation of these perception profiles, when a cryptocurrency is under attack and the benchmark otherwise, between multiple attack events of the same cryptocurrency, and between different cryptocurrencies. Our results confirm some expected overall behaviour and reactions while providing nuanced insights that may not be obvious or may even be considered surprising. Our code and datasets are publicly accessible.
Blockchain technology, often associated with cryptocurrencies like Bitcoin, holds transformative potential far beyond the realm of digital currencies. This chapter explores the diverse applications of blockchain across industries such as supply chain management, healthcare, finance, and digital identity. By leveraging its decentralized, immutable, and transparent nature, blockchain addresses critical challenges like data security, trust, and operational efficiency. The chapter delves into case studies, examining how organizations are harnessing blockchain to streamline processes, enhance security, and promote transparency. Additionally, the chapter highlights the challenges of scalability, energy regulatory hurdles consumption, that and blockchain technology faces, while envisioning its future impact on a digitally interconnected world. Whether reshaping business models or revolutionizing governance, blockchain’s evolution signifies a foundational shift in how society manages and protects data.
Cryptocurrency networks operate on decentralized systems that require efficient performance monitoring for transparency, security, and real-time insights. The establishment of a frontend-only, lightweight dashboard for displaying network metrics linked to popular digital currencies is addressed in this research paper. It collects live data from public APIs and visualizes key performance indicators such as token prices, transaction volume, and ownership distribution using open-source tools like Chart.js. The design emphasizes responsiveness, usability, and data accessibility, targeting users interested in monitoring trends and network health without backend dependencies. This dashboard simplifies data interpretation for end- users and promotes real-time decision-making.
As cryptocurrencies gain prominence in the global financial landscape, understanding the associated security risks becomes paramount. This chapter delves into the multifaceted security challenges faced by cryptocurrency users, exchanges, and blockchain networks. Key risks such as hacking, phishing, and vulnerabilities in smart contracts are explored in detail, alongside the implications of these threats on user trust and market stability. The chapter also examines various mitigation strategies, including multi-factor authentication, cold storage solutions, and robust auditing practices. By providing a comprehensive overview of both risks and preventive measures, this chapter aims to equip readers with the knowledge necessary to navigate the complex security landscape of cryptocurrencies, fostering a safer environment for digital asset transactions.
Abstract – This Blockchain technology is driving a major transformation in the healthcare industry by providing a secure and decentralized framework for managing sensitive medical records. Unlike conventional systems that rely on centralized databases—often vulnerable to cyber-attacks and unauthorized alterations—blockchain operates on a distributed ledger where recorded data is immutable. This immutability significantly enhances data integrity and reduces the risk of security breaches. A key strength of blockchain in healthcare is its ability to ensure privacy. Through encryption and decentralized control, access to medical information is restricted to authorized users only. Additionally, blockchain enables efficient and secure data sharing among hospitals, clinics, and specialists, overcoming challenges posed by fragmented or inconsistent health records. This improves the speed and accuracy of patient care. Smart contracts further enhance the system by automating access permissions and updates based on predefined rules. These self-executing protocols minimize manual intervention, reduce administrative overhead, and lower the chance of human error. Most importantly, blockchain empowers patients by giving them full control over their personal health data. Patients can choose who accesses their records, fostering transparency and trust between healthcare providers and individuals. This patient-centric approach encourages active participation in healthcare decisions and supports a more collaborative care environment. Key Words: Blockchain Technology, Medical Records Management, Decentralized Systems, Data Privacy, Smart Contracts, Patient-Centric Healthcare, Secure Data Sharing, Interoperability, Tamper-Proof Records, Healthcare Automation, Distributed Ledger, Access Control, Digital Health Transformation
The development of digital technology has encouraged the use of smart contracts as an instrument for automating agreements in Blockchain-based electronic transactions. In the context of Indonesian law, the validity of a smart contract must meet the legal requirements for an agreement, as regulated in Article 1320 of the Civil Code, which includes the agreement between the parties, legal capacity, a transparent object of the agreement, and lawful causes. Additionally, data verification in smart contracts is a key element in guaranteeing the security, authenticity, and transparency of e-commerce transactions, which is related to the provisions in the ITE Law and the PDP Law. This verification aims to prevent data manipulation, reduce the risk of fraud, and increase trust in transactions by using encryption technology, digital signatures, and Blockchain-based identity. Smart contracts can be considered valid if they fulfill the terms of the agreement and data security principles, making their use in e-commerce more effective and reliable.
Femi Oke, Samuel A Adeniji, Oyeneye Bolaji, Oladipupo Dopamu · 5 authors
Oncology care and research demand robust patient consent management to balance data sharing with privacy. This article explores a theoretical framework for implementing blockchain-based patient consent management within FHIR-compliant oncology platforms. The proposed approach integrates distributed ledger technology (using frameworks such as Hyperledger Fabric and Ethereum) with HL7 FHIR standards (including SMART on FHIR for authorization) to create a tamper-proof, interoperable consent system. We describe how patient consent directives can be recorded as smart contracts or transactions on a blockchain while remaining aligned with FHIR's Consent resource, enabling seamless data exchange across clinical and research systems. We discuss technical integration points, such as using OAuth2 (SMART on FHIR) for patient-facing consent apps and leveraging blockchain to serve as a decentralized consent registry. Key issues are examined, notably interoperability (ensuring compatibility with existing health IT and standards), privacy (protecting patient data and complying with regulations), patient empowerment (giving patients greater control and transparency), and alignment with national/international healthcare data standards and policies. Real-world examples from current literature are cited to substantiate the feasibility and advantages of this approach. The analysis indicates that a blockchain-enabled consent management system could enhance trust, security, and patient-centric control in oncology data sharing, though challenges in scalability, governance, and regulatory acceptance remain.
The article is devoted to the problem of terminological uncertainty and the lack of a unified classification of cryptocurrencies and digital assets in modern Russian legislation. Despite the adoption of Federal Law from 31.07.2020 No. 259-FZ “On Digital Financial Assets, Digital Currency and Amendments to Certain Legislative Acts of the Russian Federation”, there are many controversial issues in law enforcement practice regarding the legal status of cryptocurrencies and their place in the financial system. The article analyzes existing approaches to defining digital assets in Russian and international regulations, as well as in scientific literature. The variety of classifications and the variety of functional characteristics inherent in different types of cryptocurrencies and tokens are noted. Key contradictions between the decentralized nature of cryptocurrencies and attempts at government regulation are identified. The author’s definitions of digital currency, cryptoasset and cryptocurrency are formulated, taking into account technological, economic and legal aspects. Recommendations are proposed for improving legislation and developing agreed standards in the field of digital financial assets. The authors emphasize the need to balance the interests of the state, business, and society to ensure the successful development of the digital economy in Russia.
ABSTRACT The financial technology (Fintech) sector is undergoing a profound transformation, disrupting traditional banking models and reimagining how individuals and institutions access, manage, and utilize financial services. This thesis explores the future trajectory of Fintech with an emphasis on technological innovations, user adoption patterns, regulatory frameworks, and the sector’s broader socio-economic implications. This research aims to analyze the key drivers of Fintech evolution, including the adoption of Artificial Intelligence (AI), blockchain technology, embedded finance, and open banking systems. It also evaluates the opportunities and challenges these innovations present, particularly in the context of emerging markets like India. By using a mixed-method research approach, the study integrates primary data collected through a structured survey of 100 urban Fintech users with secondary data from authoritative industry reports, academic literature, and regulatory publications. The findings reveal that while Fintech solutions are increasingly accepted due to their convenience, speed, and personalization, issues related to cybersecurity, digital literacy, regulatory uncertainty, and trust continue to hinder mass adoption. Technologies such as AI and blockchain are identified as central to the next phase of Fintech innovation, especially in areas like digital lending, investment management, and decentralized finance (DeFi). The research concludes that the future of Fintech will be shaped not only by technological advancements but also by proactive policy-making, industry collaboration, and user education. Recommendations are offered for Fintech firms to enhance consumer trust and for policymakers to develop balanced regulatory frameworks that encourage innovation without compromising financial stability and consumer protection. The thesis contributes to the academic discourse by presenting a structured analysis of where Fintech is headed and offers practical insights for industry stakeholders, researchers, and regulators aiming to navigate this rapidly evolving landscape.
Purpose: To systematically review and synthesize existing empirical evidence on the multifaceted impacts of cryptocurrency integration on economic development and stability, aiming to determine whether its proliferation is predominantly beneficial or detrimental to sustainable economic systems. Methodology: A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Scopus database was searched for empirical articles published between 2010 and 2024, focusing on keywords related to cryptocurrencies, economic development, economic growth, financial stability, financial risks, and financial inclusion. A multi-stage filtering process led to the inclusion of 21 relevant research articles. Results: The review reveals a predominant consensus (52.4% of reviewed articles) that cryptocurrency integration has a negative impact on economic growth and stability, primarily due to volatility, systemic risks, and its use in illicit activities. While some studies highlight potential for financial inclusion (e.g., SME financing) and as a hedge in specific contexts, the broader findings point to significant challenges for monetary policy, regulatory oversight, and conventional banking paradigms. The theoretical contribution: This study consolidates fragmented research into a coherent overview, highlighting the complex and often contradictory effects of cryptocurrencies. It contributes to understanding the challenges digital currencies pose to traditional economic theories and models of financial stability, particularly within the context of achieving sustainable development. Practical implications: The findings urge policymakers to develop robust, globally coordinated regulatory frameworks to mitigate systemic risks, combat financial crime, and protect consumers. Financial institutions must adapt their risk management strategies to accommodate digital assets. The study also highlights the importance of public financial literacy programs regarding cryptocurrency risks and advocates for considering the impacts of cryptocurrency in broader economic and sustainable development planning. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure; SDG 10: Reduced Inequalities; SDG 16: Peace, Justice and Strong Institutions.
Smart contracts underpin decentralized applications but face significant security risks from vulnerabilities, while traditional analysis methods have limitations. Large Language Models (LLMs) offer promise for vulnerability detection, yet adapting these powerful models efficiently, particularly generative ones, remains challenging. This paper investigates two key strategies for the efficient adaptation of LLMs for Solidity smart contract vulnerability detection: (1) replacing token-level generation with a dedicated classification head during fine-tuning, and (2) selectively freezing lower transformer layers using Low-Rank Adaptation (LoRA). Our empirical evaluation demonstrates that the classification head approach enables models like Llama 3.2 3B to achieve high accuracy (77.5%), rivaling the performance of significantly larger models such as the fine-tuned GPT-3.5. Furthermore, we show that selectively freezing bottom layers reduces training time and memory usage by approximately 10-20% with minimal impact on accuracy. Notably, larger models (3B vs. 1B parameters) exhibit greater resilience to layer freezing, maintaining high accuracy even with a large proportion of layers frozen, suggesting a localization of general code understanding in lower layers versus task-specific vulnerability patterns in upper layers. These findings present practical insights for developing and deploying performant LLM-based vulnerability detection systems efficiently, particularly in resource-constrained settings.
This chapter considers the future of currency in light of recent developments in artificial intelligence (AI). It is now possible to put a reasonably sensible brain into every piece of money. We ask, what will intelligent money do to markets, society, and people? We first consider the ongoing digitalisation of payment and the use of blockchains in the non-fungible token space. Then we review recent advances in AI. We then discuss how these two developments come together to create “smart money” – money that has goals. Finally, we conclude with an assessment of the broader implications of smart money and how it may alter our interactions in markets and elsewhere in society.
Keamanan dan transparansi dalam sistem pemungutan suara merupakan tantangan utama dalam pemilihan elektronik atau e-voting. Penelitian ini bertujuan untuk mengimplementasikan smart contract blockchain Ethereum pada aplikasi evoting dengan tujuan meningkatkan keamanan, integritas, dan transparansi proses pemilihan. Metode penelitian yang digunakan mencakup perancangan dan implementasi smart contract, deployment pada jaringan Ethereum Sepolia, serta pengujian keamanan dan efisiensi biaya transaksi menggunakan alat seperti Remix IDE. Hasil penelitian menunjukkan bahwa penggunaan smart contract tercatat dengan transparan dan tidak bisa dimanipulasi. Namun, ada beberapa tantangan yang ditemukan seperti biaya transaksi atau gas fee yang cukup tinggi dan kompleksitas penggunaan aplikasi bagi pengguna yang belum familiar dengan teknologi blockchain. Pengujian keamanan mengidentifikasi beberapa isu yang perlu dioptimalkan, termasuk efisiensi penggunaan gas fee dan mengurangi potensi kerentanan dalam smart contract. Dengan demikian, penelitian ini dapat menjadi dasar untuk pengembangan lebih lanjut dalam penerapan sistem e-voting berbasis blockchain, khususnya untuk pemilihan skala besar seperti pemilu lokal atau nasional.
Florian Spychiger, Sabrina Wollenschläger, Matthias Hafner, Nicolas Oderbolz
Decentralized autonomous organizations (DAOs) have gained popularity over the last few years. Many projects use a DAO for community-based decisions and use a token to enable governance processes and foster participation. The setup of these tokens varies from DAO to DAO. While there are some general tokenomics frameworks, there is no DAO-specific framework including designs of multiple tokens. In this short paper, we aim at exploring the development of such DAO tokenomics framework. To unravel requirements and benefits of such a framework, we conduct interviews with six experts from the Swiss blockchain ecosystem. Switzerland is at the forefront of blockchain development and therefore well suited to serve as an exploration ground. Our results show that a DAO tokenomics framework needs to provide clear guidance while still being flexible to diverse project needs. It may bring along economic gains coupled with a risk reduction and an innovation boost for Switzerland. These benefits could be generalized to other jurisdictions making the development of a DAO tokenomics framework worthwhile.
This research paper explores the extension of COBIT 2019 into a decentralized governance framework, specifically tailored for multi-finance companies in the fintech industry. The fintech sector faces rapid technological advancements, dynamic regulatory environments, and scaling cybersecurity threats; hence, conventional governance models often do not have the flexibility and scalability to cope with these challenges effectively. It addresses these lapses by proposing a framework for governance incorporating the use of decentralized autonomous organizations, blockchain technology for transparency, and artificial intelligence for predictive risk management. The model shall be endowed with smart contracts that guarantee enforcement of compliance in an automated manner, blockchain maintenance of an unalterable audit trail, and the use of AI in finding and mitigating emerging risks in real time. These innovations are also in tune with critical COBOT 2019 domains such as MEA02 (Auditability), APO12 for Risk Management, and DSS05 for Security Services, giving them an all-encompassing and adaptive governance approach. The testing of the proposed model demonstrates significant improvement in operational resilience, regulatory compliance, and stakeholder confidence, especially within high stakes fintech environments. These findings show that incorporating emergent technologies into COBIT 2019 provides added value in governance practices and positions a scalable and future-oriented solution to help navigate the complexities of the fintech sector. This research has contributed to the development of IT governance by showing how a decentralized and technology-integrated framework can transform governance practices in ensuring agility and security within multi-finance operations.
Engin Zeydan, Josep Mangues‐Bafalluy, Şuayb S. Arslan, Yekta Türk · 5 authors
Traditional network sharing and federation models face growing challenges in ensuring secure identity management, interoperability, and trust among multiple network operators. This article presents a secure, decentralized framework that integrates self-sovereign identity (SSI) with blockchain-based consensus mechanisms to address these limitations in multivendor network-sharing environments. The proposed architecture leverages consensus models—such as Proof-of-Work (PoW), Proof-of-Authority (PoA), Practical Byzantine Fault Tolerance (PBFT), and Proof-of-Stake (PoS)—to evaluate performance tradeoffs in terms of resource consumption, consensus latency, and scalability. Experimental results show that the PBFT consensus mechanism provides the highest resource efficiency and minimal federation latency overhead when integrating SSI. In contrast, Cosmos PoS offers a balanced tradeoff between scalability, throughput, and moderate resource utilization, making it well-suited for future federated network deployments that require interoperability and high transaction capacity. In addition, threat models along with security and privacy considerations are addressed to ensure compliance with the General Data Protection Regulation (GDPR) and to support data sovereignty.
Blockchain's economic value lies in enabling financial and economic transactions without relying on trusted, centralized intermediaries. In practice, however, transactions pass through a fragmented chain of intermediaries before being included on-chain. Because standard blockchain data reveal only the winning block, this process is largely unobservable. We address this limitation by constructing a novel dataset of 15,097 non-winning Ethereum blocks, that is, blocks proposed but not selected for inclusion. We show that 21% of user transactions are delayed: they appear in candidate blocks but not in the winning block, implying that fragmented routing materially affects inclusion time. We further show that execution quality varies substantially across candidate blocks: for the same swap, both execution probability and execution price differ across proposed blocks. To study these differences, we examine competition between two arbitrage bots trading between decentralized and centralized exchanges. We find that, conditional on inclusion in a block that also contains transactions from these bots, user swaps in the same (opposite) direction are less likely (more likely) to execute and receive worse (better) prices. These results show that routing and block composition are central determinants of execution quality and market quality in on-chain markets.
Smart contracts are computer programs that run on blockchain platforms, with Solidity being the most widely used language for their development. As blockchain technology advances, smart contracts have become increasingly important across various fields. In order for smart contracts to operate correctly, the correctness of the compiler is particularly crucial. Although some research efforts have been devoted to testing Solidity compilers, they primarily focus on testing methods and do not address the core issue of generating test programs. To fill this gap, this paper designs and implements Solsmith, a test program generator specifically aimed at uncovering defects in Solidity compilers. It tests the compiler correctness by generating valid and diverse Solidity programs. We have designed a series of unique program generation strategies tailored to Solidity, including enabling optimizations more frequently, avoiding undefined behaviour, and mitigating behavioural differences caused by intermediate representations. To validate the effectiveness of Solsmith, we assess the effectiveness of the test programs generated by Solsmith using the approach of differential testing. The preliminary results show that Solsmith can generate the expected test programs and uncover four confirmed defects in Solidity compilers, demonstrating the effectiveness and potential of Solsmith.