Blockchain Papers

Jinli Wang, Hang Zhao, Mengzhuang Liu, Zehui Yuan · 8 authors

No abstract is available for this record.

Алтынзер Байганова, Әли Асылбек, Абиболла Сейтбек

В статье рассматриваются аспекты применения технологии блокчейн в сфере образования. Описаны основные принципы работы блокчейна, его механизмы безопасности и преимущества децентрализации. Особое внимание уделено смарт-контрактам и их использованию для автоматизации образовательных процессов. Также рассмотрены примеры применения технологии для хранения дипломов, сертификации, учета академических достижений и управления стипендиями. Обсуждаются преимущества и вызовы внедрения блокчейна, а также перспективы его развития в образовательной среде на основе мирового опыта. Практическая значимость данного исследования заключается в применении технологии блокчейн для упрощения проверки подлинности документов, автоматизации образовательного процесса и обеспечения безопасности данных. В данной статье рассмотрены теоретические основы и конкретные примеры применения технологии блокчейн в сфере образования, разработан элективный курс по информатике «Технологии Web3».

Alexander Wu

Abstract Increased and sustained access to the formal financial system enables communities to better meet their basic needs, prepare for and respond to unexpected shocks, and achieve broader economic growth. Yet many emerging economies like those across Latin America continue to face barriers that prevent individuals, households, and businesses from accessing the formal financial system. Financial inclusion efforts that leverage technological innovation are well suited to address some of them. Specifically, fintech products built on blockchains offer new ways to access financial services by creating pathways that do not rely on traditional infrastructure. Blockchain-based services offer easier financial access, innovative credit opportunities, and capital formation in a decentralized financial environment. While blockchain and DeFi are still in their early stages, these services have the potential to close some persistent gaps that stand in the way of more inclusive Latin American economies.

Umna Iftikhar, Hafiz Muhammad Attaullah, Inam Ullah Khan, Muhammad Mansoor Alam · 6 authors

Verification of a qualification, achievement, quality, or aspect of a person’s background is one of the biggest problems nowadays as we have seen many platforms where students can get fake credentials. Every organization must select professional and academically qualified employees to give quality service. As a result, corporations rely on academic certifications to confirm and measure their prospective employees’ academic qualifications. On the other hand, these employers lack a standardized process for confirming the legitimacy of academic certificates or degrees. Because the present procedures for verifying educational certifications are time-consuming, exhausting, and costly, just a few employers verify certificates for prospective employees. This research examines the issues that are related to the smart verification of someone’s credentials. To make the process of verifying digital credentials quicker, simpler, and more cost-effective, we suggest decentralized architecture. We present the prototype, design, and implementation of the proposed framework.

Shayan Firouzian-Haji, SeyedEmran Eshghollahi, Matineh Ziari, Reza Tavakkoli‐Moghaddam · 5 authors

No abstract is available for this record.

Mohammad Hadi Andalib, Ahmad Shabani

1. Introduction and ObjectiveInformation asymmetry has long been recognized as a critical challenge within financial markets, where unequal access to information between contracting parties can lead to inefficient outcomes. In the context of Islamic finance, this issue manifests most prominently through adverse selection and moral hazard, both of which are substantially intensified in profit-and-loss sharing arrangements. Participatory contracts such as Mushārakah and Muḍārabah rely on mutual trust, transparency, and aligned incentives. However, empirical evidence from Islamic banking practice—particularly in Iran—shows that actual utilization of these contracts remains limited. Banks frequently avoid participatory financing and shift toward fixed-return modes (such as Murābaḥah), mainly due to the heightened risk of borrower default arising from information asymmetry, insufficient visibility into business operations, and difficulties in monitoring managerial behavior. Within this environment, adverse selection emerges before contract formation when the bank cannot accurately distinguish between high-quality and low-quality project proposals or entrepreneurs. This may result in the unintended approval of risky proposals, thereby elevating the likelihood of non-performing financing. The problem is further accentuated by limitations in credit assessment processes, inadequate transparency in project data, and disparity in profit expectations and execution approaches between banks and entrepreneurs. Recent advances in decentralized technologies—particularly Web3 architectures incorporating blockchain, decentralized identity frameworks, distributed ledgers, and programmable smart contracts—provide new opportunities to address these long-standing informational and contractual challenges. Web3 offers a structural shift from centralized information control to transparent and verifiable records shared within a network of stakeholders. Such transparency can diminish information asymmetry, reduce opportunities for misrepresentation, automate contract enforcement, and improve the reliability of credit histories. The primary objective of this research is to assess the feasibility of reducing default risk caused by adverse selection in Islamic participatory contracts through the application of Web3 technology. The study aims to: (1) Identify the core factors that generate adverse selection in participatory financing, (2) Evaluate the strength and direction of their influence on default risk, and (3) Analyze how Web3 mechanisms can mitigate these factors and enhance the practical viability of participatory contracts in Islamic banking systems.2. Methods and MaterialsThis research adopts a mixed-methods exploratory–confirmatory design. Owing to the complexity and conceptual novelty of integrating Web3 systems with Islamic financial contracts, the study began with a qualitative phase followed by quantitative model testing. Qualitative Phase: Delphi MethodThe qualitative stage employed a three-round Delphi process to identify and validate the principal determinants of adverse selection in participatory financing. The expert panel comprised university scholars in Islamic economics, senior managers of credit and risk departments in Iranian banks, and professional consultants in Islamic financial technology. The first round used open-ended questionnaires to collect diverse expert insights, resulting in an initial list of thirteen candidate factors. In the second round, a structured Likert-scale survey assessed the significance of the proposed factors. Consensus criteria were set at mean ≥ 3.5 and standard deviation ≤ 1, consistent with established Delphi methodology. In the final round, experts confirmed the final factor set, which consolidated into three primary constructs: (1) Lack of transparency in customer information, (2) Insufficient evaluation of the entrepreneur’s technical competence, and (3) Misalignment of objectives between financing partners. These validated constructs provided the basis for the structural model.Quantitative Phase: PLS-SEM AnalysisIn the second phase, a structured questionnaire was administered to 289 participants representing the same expert categories. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. PLS-SEM was chosen due to:- The predictive and exploratory nature of the research,- The inclusion of higher-order and formative construct, and- Potential non-normality in expert response distributions. Model evaluation followed established metrics, including reliability (Cronbach’s alpha and composite reliability), convergent validity (AVE), discriminant validity, and structural path significance (t-statistics and p-values). Multi-collinearity was assessed using VIF values, all of which were below the acceptable threshold. Confidence levels were set at 95% with corresponding significance thresholds of p < 0.05.3. Research FindingsThe results of the structural model confirm that adverse selection exerts a direct and significant positive effect on default risk in participatory contracts (β = 0.299, p < 0.01). The components of adverse selection are strongly driven by:- Lack of transparency in customer information (β = 0.932, p < 0.001),- Misalignment of objectives between partners (β = 0.887, p < 0.001), and- Insufficient assessment of entrepreneurial competence (β = 0.885, p < 0.001). This highlights that default risk in participatory financing is not merely a result of financial capacity constraints, but is deeply rooted in information imbalances and strategic behavior at the contract initiation stage. The model further demonstrates that Web3 technologies have a significant mitigating influence. The path coefficient for Web3’s direct effect on reducing default risk is negative and statistically meaningful (β = −0.214, p < 0.01). Additionally, Web3 reduces the negative effects of adverse selection and information asymmetry, as shown by reversed and weakened path effects in the Web3-enhanced environment. Key Web3 mechanisms enabling this outcome include:- Real-time transparency and immutable information records,- Smart contracts that automate profit-sharing and enforce commitments,- Decentralized digital identity (DID) systems that support reliable, tamper-proof credit histories,- Tokenization of collateral and tangible/ intangible assets, enabling verifiable and liquid security guarantees,- Reduced monitoring and enforcement costs due to auditability of on-chain transactions. 4. Discussion and ConclusionThe findings of this research indicate that the primary barrier to effective participatory financing in Islamic banking is not merely structural or regulatory, but fundamentally informational. Adverse selection emerges where transparency, competence assessment, and goal alignment are weak. Conventional mechanisms—such as collateralization and post-contract supervisory audits—provide only partial and reactive mitigation. In contrast, Web3 offers a proactive and systemic solution by embedding transparency, verifiability, and automated compliance directly into the contract infrastructure. By shifting the reliance from personal trust to systemic trust, Web3 supports the original normative philosophy of Islamic finance: equitable profit-and-loss sharing, partnership-based financing, and ethical allocation of capital. From a policy perspective, adopting Web3 frameworks may substantially increase the feasibility and attractiveness of participatory financing modes for Islamic banks that currently avoid them due to high default exposure. This study contributes to the academic discourse on risk management in Islamic finance by demonstrating a structural linkage between information theory, contract design, and emerging decentralized technological capabilities. Practically, the research proposes a hybrid risk-management strategy, integrating traditional credit evaluation frameworks with Web3-based transparency, identity assurance, and automated enforcement. Future work should examine regulatory, Shariah governance, cybersecurity considerations, and interoperability standards needed to implement Web3-based participatory financing systems at scale. Nonetheless, the present results indicate that intelligent and compliant adoption of Web3 can significantly reduce default risk and enable the revival of participatory financing models in Islamic banking.

P. E. S. N. Krishna Prasad, Preeti Chandrakar, Vipin Kumar Nayak

No abstract is available for this record.

Pritam Rani, Prity Rani, Prity Rani, Prity Rani · 7 authors

No abstract is available for this record.

V. Hemamalini, M. Jeyaselvi, Amit Kumar Tyagi, Shabnam Kumari

Decentralized Applications (dApps) and Distributed Ledger Frameworks (DLFs) represent critical advancements in the realm of blockchain technology, promising enhanced security, transparency, and efficiency. Decentralized Applications, leveraging the inherent properties of blockchain, operate without central control, offering users greater autonomy and reducing reliance on intermediaries. These applications span various domains, from finance and supply chain management to gaming and social networks, demonstrating the versatility and transformative potential of dApps. Distributed Ledger Frameworks, encompassing both blockchain and non-blockchain-based systems, provide the underlying architecture for these applications. DLFs ensure data integrity, immutability, and consensus across distributed nodes, fostering a trustless environment where participants can transact securely. Key frameworks like Ethereum, Hyperledger, and Corda offer diverse features tailored to different use cases, ranging from public, permissionless networks to private, permissioned systems.

Stefan Kitzler, Masarah Paquet-Clouston, Bernhard Haslhofer

The Decentralized Finance (DeFi) ecosystem has experienced over \$10 billion in direct losses due to crime events. Beyond these immediate losses, such events often trigger broader market reactions, including price declines, trading activity changes, and reductions in market capitalization. Decentralized Autonomous Organizations (DAOs) govern DeFi applications through tradable governance assets that function like corporate shares for voting and decision-making. Leveraging DeFi's granular trading data, we conduct an event study on 22 crime events between 2020 and 2022 to assess their economic impact on governance asset prices, trading volumes, and market capitalization. Using a dynamic difference-in-differences (DiD) framework with counterfactual governance assets, we aim for causal inference of intraday temporal effects. Our results show that 55% of crime events lead to significant negative price impacts, with an average decline of about 14%. Additionally, 68% of crime events lead to increased governance asset trading volume. Based on these impacts, we estimate indirect economic losses of over $1.3 billion in DAO market capitalization, far exceeding direct victim costs and accounting for 74% of total losses. Our study provides valuable insights into how crime events shape market dynamics and affect DAOs. Moreover, our methodological approach is reproducible and applicable beyond DAOs, offering a framework to assess the indirect economic impact on other cryptoassets.

Ch Sree Kumar, Akhilendra Pratap Singh, K. Hemant Kumar Reddy

No abstract is available for this record.

Lei Wang, Yan‐jun Mi, Yanan Zhang, Jialin Zhang

No abstract is available for this record.

Armin Reiter

Web3 is a fundamental change from a centralized, platform-centric internet to a decentralized, user-owned ecosystem powered by an open-source technology called Blockchain. This shift is not just a technological evolution, but also changes significantly how value is created, delivered, and captured. It enables new products, innovations, and business models. These products are often powered by tokens, whose value is described by their underlying tokenomics. They are designed to engage the community and incentivize the people who interact with the project. The users of Web3 often come together in decentralized autonomous organizations and democratically decide on the next steps and essential developments of the organization. The business models that are now possible because of the capabilities of a decentralized web have different success factors and reasons why they fail. This thesis conducts a systematic literature review and qualitative expert interviews to identify the success factors of Web3 business models. It first lists and categorizes the prevalent Web3 business models, their structures, and revenue models, and then highlights the success factors for Web3 business models. The findings reveal the difference between Web2 and Web3 business models, highlighting the importance of community, decentralization, governance, and robust token economics.

Hassan Atwi, Tom Lichtenstein, Cesare Pautasso, Mathias Weske

No abstract is available for this record.

Wenyang Jia, Jingjing Wang, Kai Lei

Modern blockchains need fast, reliable propagation to balance security and throughput. Virtual-coordinate methods speed dissemination but rely on slow iterative updates, leaving nodes out of sync. We present BlockSDN-VC, a transaction-broadcast protocol that centralises coordinate computation and forwarding control in an SDN controller, delivering global consistency, minimal path stretch and rapid response to churn or congestion. In geo-distributed simulations, BlockSDN-VC cuts median latency by up to 62% and accelerates convergence fourfold over state-of-the-art schemes with under 3% control-plane overhead. In a real blockchain environment, BlockSDN-VC boosts confirmed-transaction throughput by 17% under adversarial workloads, requiring no modifications to existing clients.

Dominik Apel, Zeta Avarikioti, Matteo Maffei, Yuheng Wang

Rollup protocols have recently received significant attention as a promising class of Layer 2 (L2) scalability solutions. By utilizing the Layer 1 (L1) blockchain solely as a bulletin board for a summary of the executed transactions and state changes, rollups enable secure off-chain execution while avoiding the complexity of other L2 mechanisms. However, to ensure data availability, current rollup protocols require the plaintext of executed transactions to be published on-chain, resulting in inherent privacy limitations. In this paper, we address this problem by introducing Calyx, the first privacy-preserving multi-token optimistic-Rollup protocol. Calyx guarantees full payment privacy for all L2 transactions, revealing no information about the sender, recipient, transferred amount, or token type. The protocol further supports atomic execution of multiple multi-token transactions and introduces a transaction fee scheme to enable broader application scenarios while ensuring the sustainable operation of the protocol. To enforce correctness, Calyx adopts an efficient one-step fraud-proof mechanism. We analyze the security and privacy guarantees of the protocol and provide an implementation and evaluation. Our results show that executing a single transaction costs approximately $0.06 (0.00002 ETH) and incurs only constant-size on-chain cost in asymptotic terms.

Federico P. Cortese, Antonio Pievatolo, Elisa Maria Alessi

Statistical jump models have been recently introduced to detect persistent regimes by clustering temporal features and discouraging frequent regime changes. However, they are limited to hard clustering and thereby do not account for uncertainty in state assignments. This work presents an extension of the statistical jump model that incorporates uncertainty estimation in cluster membership. Leveraging the similarities between statistical jump models and the fuzzy c-means framework, our fuzzy jump model sequentially estimates time-varying state probabilities. Our approach offers high flexibility, as it supports both soft and hard clustering through the tuning of a fuzziness parameter, and it naturally accommodates multivariate time series data of mixed types. Through a simulation study, we evaluate the ability of the proposed model to accurately estimate the true latent-state distribution, demonstrating that it outperforms competing approaches under high cluster assignment uncertainty. We further demonstrate its utility on two empirical applications: first, by automatically identifying co-orbital regimes in the three-body problem, a novel application with important implications for understanding asteroid behavior and designing interplanetary mission trajectories; and second, on a financial dataset of five assets representing distinct market sectors (equities, bonds, foreign exchange, cryptocurrencies, and utilities), where the model accurately tracks both bull and bear market phases.

Mahdi Salehi, Homa Molavi

Purpose This study aims to investigate the potential benefits of blockchain technology in enhancing corporate accountability and reporting transparency to foster a more optimistic view toward its implementation in business practices. Design/methodology/approach Data were gathered from 304 managers, accountants, auditors and board members of small and medium-sized enterprises in Razavi Khorasan Province 2024. A combination of standardized instruments and a custom-developed questionnaire validated by experts was used to measure the variables. The data were analyzed using SmartPLS. In the proposed model, blockchain adoption and reporting transparency are independent variables, while corporate accountability and reporting quality are dependent variables. Findings The analysis reveals that implementing blockchain technology has a strong positive impact on corporate accountability and financial reporting quality. In addition, higher levels of transparency in reporting are associated with improved organizational responsiveness, suggesting that greater openness in information disclosure strengthens companies’ ability to respond to stakeholder demands and regulatory expectations. The results indicate that adopting blockchain can significantly contribute to more reliable, timely and transparent corporate reporting practices. Originality/value This research offers a novel empirical perspective on how blockchain can transform corporate accountability frameworks. It emphasizes the importance of technological trust, transparency and continuous blockchain-based auditing in advancing corporate governance. The study provides practical recommendations for managers, regulators and policymakers to support blockchain implementation through regulatory measures, security protocols and inter-organizational collaboration. Ultimately, these findings reinforce stakeholder trust, regulatory compliance and long-term organizational credibility.

Stijn Van Hijfte

No abstract is available for this record.

B S Sunitha, S. Saravana Kumar

Healthcare data management in cloud environments faces critical challenges in balancing security, privacy, operational efficiency, and regulatory compliance, as traditional access control mechanisms are inadequate for addressing the complex, multi-tenant, and dynamic nature of modern cloud infrastructures handling sensitive Electronic Health Records (EHRs). This paper introduces a novel hybrid framework that integrates Attribute-Based Access Control (ABAC) with Ethereum blockchain technology to establish a comprehensive multi-layered security architecture for cloud-based healthcare systems, combining advanced cryptographic techniques including double encryption using AES and RSA algorithms, Shamir's Secret Sharing for key management, smart contracts for automated policy enforcement, and multi-party computation protocols to ensure privacy preservation without compromising system performance. Extensive experimental evaluation conducted using 4,412 anonymized clinical records with 12 distinct attributes demonstrates exceptional efficiency with average record insertion time of 1.90 ms, retrieval time of 0.14 ms, blockchain mining time of 0.01 seconds, and hybrid architecture throughput of 562.94 records/second with 1.78 ms latency, significantly outperforming traditional centralized systems (337.17 rec/s, 2.97 ms) and pure blockchain implementations (3.37 rec/s, 296.98 ms). Security assessments reveal 100% operational reliability, 97.3% policy violation detection accuracy, 89% reduction in unauthorized access attempts, and comprehensive regulatory compliance with HIPAA (97%), GDPR (92%), ISO 27001 (94%), and SOC 2 (89%) standards, while maintaining optimized system resource utilization with CPU usage at 35.6%, memory at 48.0%, and network I/O at 34.1%. The framework addresses key limitations of existing approaches by providing seamless integration across multiple cloud layers, eliminating single points of failure, ensuring data immutability through distributed consensus mechanisms, maintaining comprehensive audit trails, and offering practical implications for healthcare organizations seeking secure, scalable, and compliant data sharing mechanisms in cloud-native environments, thereby contributing to the advancement of secure healthcare informatics by bridging the gap between theoretical access control models and practical implementation requirements in distributed cloud infrastructures.

Chang Li, Huijuan Zhu, Qiang Zhou, Shiyu Gan · 5 authors

As security concerns in blockchain platforms continue to rise, triggered by substantial financial losses, detecting vulnerabilities in smart contracts has emerged as a crucial focus for both academia and industry. Although many promising vulnerability detection methods for Ethereum have been proposed in recent years, their long-term reliability and adaptability across different versions of smart contracts remain unresolved. Specifically, the performance of these methods tends to degrade over time, and in some cases, they may even fail entirely. A key factor contributing to this dilemma is the regular updates of Solidity versions. These updates often introduce new features or syntax changes, which significantly influence how vulnerabilities are manifested and detected. To tackle this challenge, we propose Triplet Detection (TD), a triplet learning-based vulnerabilities detection framework, to preserve invariant vulnerability knowledge across multiple Solidity versions. In TD, we propose a novel Smart Offline Mining (SOM) strategy to guide triplet selection, ensuring the learned embedding capture both foundational and version-independent vulnerability features. The experimental results demonstrate that TD outperforms state-of-the-art vulnerability detection tools and baseline methods. Furthermore, TD achieves superior performance in detecting vulnerabilities across different versions of smart contracts (e.g., from v0.4 to v0.8), highlighting its capability to tackle the challenges of long-term reliability and adaptability in detection models due to the updates of smart contract versions.

Rogério Figurelli

We step outside the P = NP vs. P ≠ NP dichotomy and, following a co-evolutionary, hypothesis-first program, we frame evidence by the accounting constraint P(L, t) + NP(L, t) = 1, where t indexes registered time windows and L indexes structural layers of analysis. The credit assigned to constructive computation P(L, t) versus certificate-based reasoning NP(L, t) may shift across windows and layers, but their sum is conserved by design. Within this multilayer, time-indexed lens, we propose a test object for proof in 3-SAT: a small, auditable branching set K. Our operational hypothesis is that, within controlled experimental windows, there exists K ⊆ V(F) with |K| ≤ c·log n such that, for every partial assignment α: K → {0,1}, the restricted formula F ∣ α terminates in polynomial time and emits a publicly verifiable certificate (a satisfying assignment or a DRAT/DRUP-style unsatisfiability proof). Because 2^|K| = n^O(1), exhaustive branching over K is polynomial inside the window, enabling artifact-backed constructive behavior without asserting a universal algorithm. We (i) define auditable objects and falsifiable hypotheses, (ii) sketch a π-rounds normalization pipeline that contracts structure while logging transformations, (iii) posit a finite catalog of local obstructions with radius-2 witnesses, (iv) outline a greedy hitting-set routine to assemble K, and (v) introduce protection mechanisms against recovery of K by an adversary (commitments and zero-knowledge). Evidence will be supplied via reproducible artifacts (DRAT logs, commitments, run ledgers) and transport tests across registered windows and layers, and will be interpreted under the constraint P(L, t) + NP(L, t) = 1, in a manner consistent with kernelization barriers and sparsification limits.

Hetansh Shah, Himangi Agrawal, Dhaval Shah

No abstract is available for this record.

Ruben M Nayve Jr, Ferdinand Timbang, Mark Anthony Pelegrin

This study investigates the role of network effects in shaping economic value creation within cryptocurrency ecosystems. While cryptocurrencies have evolved from speculative assets into complex digital platforms that facilitate transactions, decentralized finance, and governance, their economic sustainability is fundamentally driven by the dynamics of user adoption and interconnectivity. Drawing upon theories of network externalities and digital platform economics, this research employs a mixed-methods approach that integrates quantitative econometric modeling with qualitative analysis of policy and industry practices. Quantitative data, including market capitalization, transaction volume, wallet addresses, and hash rate, are analyzed to measure the correlation between network growth and value creation. Complementary qualitative insights are derived from literature reviews and expert interviews to contextualize the findings within broader regulatory and technological frameworks. The results reveal that network size and user activity exert significant positive effects on value creation, with evidence of nonlinear threshold dynamics: once a critical mass of adoption is reached, economic value accelerates disproportionately. Comparative analysis across major ecosystems such as Bitcoin and Ethereum highlights differences in how network effects interact with technological innovation and governance structures. The findings contribute to advancing theoretical understanding of digital network economies and provide practical insights for stakeholders, including developers, investors, and policymakers. By identifying both opportunities and risks, particularly regarding volatility and regulatory challenges, this study offers a comprehensive framework for evaluating the long-term sustainability of cryptocurrency ecosystems.