Blockchain Papers

Kothai G, Ashrut Sharma, Ritam Pal

No abstract is available for this record.

Christopher G. Harris

No abstract is available for this record.

Hangbin Shen, Yong Shen, Shenjie Xu, Binbin Du

No abstract is available for this record.

Stefan Kitzler

Decentralized Finance (DeFi) represents an emerging financial ecosystem that offers services such as lending, investing, and trading without traditional intermediaries like banks or financial institutions. Unlike conventional financial systems, users interact directly with software programs called smart contracts that encode financial logic and automate service delivery. This novel ecosystem promises transparency through public blockchain ledgers that make all transactions visible and inclusion through open access that eliminates traditional barriers to financial participation. Additionally, DeFi enables decentralized governance where users participate in protocol decision-making, and smart contracts facilitate advanced financial engineering through compositional service integration. However, despite these technical innovations, DeFi introduces significant challenges related to transaction complexity, governance concentration, and cybersecurity vulnerabilities that undermine its foundational promises. This thesis develops computational methods to systematically investigate these challenges in Decentralized Finance through empirical analysis of blockchain data. First, to address the complexity of DeFi compositions, we developed an algorithm that extracts fundamental building blocks from individual transactions, revealing recurring patterns and hidden interdependencies between financial services and assets that manual analysis cannot capture at scale. Second, we applied network analysis techniques and introduced novel measurements to examine the governance structures of decentralized applications, focusing on contributors with development and administrative roles. Our analysis revealed common voting patterns and centralized decision-making that contradict claims of decentralized governance. Third, we adapted a difference-in-differences statistical framework to quantify the economic impact of cybercrime on governance tokens, demonstrating that indirect effects on prices and trading volumes significantly exceed the direct losses suffered by immediate victims. These computational methods collectively provide the first systematic, large-scale analytical framework for empirically investigating DeFi ecosystems, revealing fundamental gaps between theoretical promises of transparency and inclusion and practical realities. The findings have significant implications for researchers, policymakers, and practitioners by establishing evidence-based approaches to measuring decentralization claims and systemic risks in blockchain-based financial systems.

Christopher G. Harris

No abstract is available for this record.

Ahmad Ahmad, Muhammad Said, Abdillah Abdillah, Abdulloh Munir

The rapid expansion of Decentralized Finance (DeFi), powered by blockchain technology, has transformed global financial systems by offering peer-to-peer, intermediary-free services. However, its compatibility with Islamic economic law (hukum ekonomi syariah) remains uncertain due to potential violations of Sharia principles such as the prohibition of riba (usury), gharar (excessive uncertainty), and maysir (speculation). This study addresses this gap by employing a qualitative maqāṣid al-sharī‘ah-based analysis to assess the alignment of DeFi mechanisms decentralized exchanges, lending protocols, and smart contracts with Islamic ethical and legal values. Data were collected through literature review and document analysis from classical Islamic sources, fatwas, and current DeFi documentation. The findings show that while many DeFi practices contain non-compliant elements, their underlying technology particularly smart contracts and decentralized governance holds significant potential for adaptation. When structured using Sharia-compliant contracts such as murābaḥah, mushārakah, or wakālah, and guided by maqāṣid objectives like ḥifẓ al-māl (preservation of wealth) and ḥifẓ al-dīn (preservation of faith), DeFi can support financial inclusion, transparency, and justice in accordance with Islamic law. This study proposes a normative framework for building Sharia-compliant DeFi platforms, integrating technical innovations with ethical governance, thereby offering a transformative model for Islamic finance in the digital era.

Maurantonio Caprolu, E. Onofri, Omar Eldesouky, Roberto Di Pietro

No abstract is available for this record.

Adaora. A, Obayi, Caroline Asogwa, Blessing .C. Uzo

This study investigates traditional health care delivery systems to eliminate current inefficiencies by creating a decentralized appointment and referral management system using Web 3.0 technology, blockchain, smart contracts, and Decentralized Identity (DID) compatible with scalable cloud storage. In a series of multi-agent simulations run on the Ethereum and Polygon Testnets, the performance of the system under simulated high-load traffic scenarios was tested. The simulation results showed consistent transaction latencies (285 ms average), high throughput rates (34 appointments per second), and low errors rates (1.4%). Another innovation of this study was the development of a hybrid architecture that enables the storage of cryptographic hashes associated with medical records on-chain, while keeping patient data encrypted on off-chain servers. This allows the immutability and auditability of the data while still maintaining compliance with GDPR and HIPAA regulations by enabling patient data to be deleted from the system entirely. As a result, this system was significantly more secure, transparent, and operationally efficient compared to current centralized systems. These findings confirm and support the potential of decentralized technologies for Scalable, Trustworthy Medical Service Delivery of the Data.

Bhargav Chickmagalur Nanjundappa

No abstract is available for this record.

Donghwa Seo, Kyoung-Kuk Kim

This paper analyzes transaction fees on blockchains by considering that they form a priority queue and users play a queueing game. Using an M/G^K/1 priority queue model, we provide new insights into the dynamics governing transaction fees and their impact on user behavior. We derive semi-closed form expressions for steady-state quantities and extend the relationship between user delay costs and transaction fees to general block generation times. We apply the model to the Bitcoin network and simulate user responses under various scenarios. Cross-chain analysis across Bitcoin, Dogecoin, and Litecoin reveals similarities in normalized cost structures.

Dylan Sandfelder, Mihai Cucuringu, Xiaowen Dong

Real temporal interaction streams carry predictive structure in short-horizon motif patterns -- repetition, reciprocity, star diversity, triadic flow -- that vanilla temporal graph neural networks (TGNNs) often fail to expose to their edge scorers. We show this concretely on MOOC interaction prediction, where a small four-feature family of past-window star counts already delivers most of the lift over a strong static GNN. Across a wide set of real and synthetic temporal datasets we find that motif activity organizes consistently along three scale-stable axes (dyadic recency/reciprocity, star diversity, triadic flow), and we use this empirical structure to design a compact 13-coordinate, leakage-safe, candidate-local motif feature map h(u, v, t) that linearly embeds into any static or temporal encoder without architectural changes. A temporal Weisfeiler-Leman (WL) analysis places the augmentation relative to the first level of an anchored temporal-WL hierarchy and exhibits a candidate-anchored pair on which motif features distinguish. We demonstrate empirically that the same augmentation consistently lifts performance across heterogeneous tasks: TGB link-property prediction across all five baselines, edge classification on Bitcoin Alpha/OTC and MOOC, and graph-level classification of synthetic temporal generators.

Rischan Mafrur

Real-world asset tokenization is often presented as a mechanism for improving the liquidity of traditionally illiquid assets. However, on-chain representation and secondary-market liquidity are distinct outcomes. This paper examines whether tokenized real-world assets exhibit meaningful observed liquidity and identifies the token characteristics associated with higher market activity. Using token-level data from RWA.xyz and supplemental contract-level observations from Etherscan, the study constructs an Ethereum-based monthly panel of non-stablecoin real-world assets across three prominent categories: U.S. Treasury-backed tokens, gold-backed commodity tokens, and private-credit-related tokens. Liquidity is measured using turnover, active addresses, and an active-month indicator. The empirical design combines descriptive statistics, non-parametric group tests, and exploratory panel regressions suited to short and sparse token histories. The results show substantial heterogeneity across asset categories. Gold-backed tokens exhibit broader holder bases and more persistent on-chain activity than many Treasury and private-credit-related products, while outstanding asset value alone does not reliably predict observed liquidity. The paper contributes to the literature by developing a clearer empirical measurement framework for real-world-asset liquidity and showing that tokenization and liquidity should be analyzed as distinct outcomes.

Khire Rushikesh Ulhas, Khemraj Sharma

ABSTRACT Globalization, multi‐tier supplier networks and demands for transparency and accountability have made supply chain management more complex than ever. Traditional supply chain systems are often characterized by limited visibility, fragmented data sharing, and security vulnerabilities leading to inefficiency and distrust. Collaboration between IoT and Blockchain to Enhance Supply Chain Operations Imagine having products that can be tracked in real time, data being stored securely through distributed ledgers, and transactions performed automatically using smart contracts. The Internet of Things gathers data throughout all the phases in supply chain life and blockchain technology guarantees that it is authentic and also unchangeable. This innovative solution exhibits significant advancements in transparency, security, and operational efficiency when compared with existing supply chain approaches. These results confirm that supply chain systems powered by blockchain technology can improve transaction speed, traceability and integration, while minimizing operational risk. Thus, this work provides a dependably transferable and scalable method to increasing supply chain traceability and efficiency.

Byung-Mun LEE

본 연구는 블록체인 기반 스마트계약의 국제물품매매계약에 관한 유엔협약(CISG)의 적용가능성과 적용상 주요 쟁점을 분석하는 데 목적이 있다. 스마트계약은 무역거래의 비용·시간·불이행 위험을 줄일 수 있는 장점이 있으나, 법적·제도적 기반의 미비로 인해 활용이 제한되고 있다. 이에 본 연구는 스마트계약의 개념과 유형을 검토하고, CISG의 장소적·인적·거래유형 및 물적 적용범위 측면에서 스마트계약의 적용가능성을 분석하였다. 또한 자연어 계약과 프로그램 코드 간 충돌 문제 및 암호화폐 지급의 법적 성격 등을 중심으로 CISG 적용상 쟁점을 검토하였다. 연구 결과, 스마트계약은 CISG의 유연한 해석을 통해 규율 범위 내에 포함될 수 있으며, 계약 해석에 있어 당사자의 의사와 전문성이 중요한 기준이 됨을 확인하였다. 나아가 스마트계약의 활성화를 위해서는 국제적 통일해석과 실무적 가이드라인의 정비가 필요함을 시사한다.

Andi Aidir Arsy, Dewi Salmita, Muhammad Syafaat, Noval · 5 authors

Purpose - This study examines the association between regional investment, leverage, and regional financial independence within the fiscal decentralization framework. Design/methodology/approach - A quantitative associative approach is employed using pooled panel data from 13 regency and municipal governments in Central Sulawesi Province during 2018–2024. The relationships among variables are analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with WarpPLS. The analysis is grounded in fiscal decentralization theory and agency theory to explain local government financial management behavior. Finding/Results – The results indicate that regional investment and leverage are positively and significantly associated with regional financial independence in the pooled PLS-SEM model. Long-term investment is related to stronger fiscal capacity, while leverage may serve as a supportive financing instrument when managed prudently. Together, both variables explain a moderate proportion of the variation in regional financial independence. Originality/Value - This study contributes empirical evidence on how regional investment and leverage are linked to local fiscal autonomy in Central Sulawesi, an underrepresented provincial context in Indonesian local government finance studies. The findings provide practical insights for local governments to improve productive long-term investment and maintain prudent liability management. This study is limited to one province and two explanatory variables; therefore, future research may expand regional coverage and include governance quality, revenue effectiveness, transfer dependence, and expenditure efficiency.

Marc Aliaga Borras

By chance or by destiny, Bitcoin mining companies have found themselves with a golden opportunity in their hands: they possess the most scarce asset of the 21st century—energy. Something similar happened back in the mid-19th century, railroad companies acquired millions of acres of land and rights-of-way strictly to lay down train tracks with the main idea of a business fundamentally focused on physical transportation. However, when the telegraph was invented, they realized that the optimal location to deploy electrical communication lines was right alongside those very train tracks. They already possessed the cleared terrain, the physical security, and the legal rights-of-way. And as we have seen, the structural mispricing identified in this thesis represents a finite, high-velocity arbitrage window. Where currently, Wall Street's evaluation models remain anchored to old crypto-mining frameworks, valuing these entities on cyclical hash-rate economics rather than the long-duration infrastructure value of their underlying energized grid connections.

С. А. Попель

The article examines the economic essence of asset tokenization as a new form of microeconomic relations in the context of financial market digitalization. The existing approaches to interpreting the concept of "asset tokenization" in domestic and foreign scientific literature are generalized, and the author's definition of this economic category is proposed as an institutional-technological mechanism for digitalizing property rights that forms a new architecture of microeconomic relations among market participants. The existing approaches to the classification of tokenized assets are analyzed, in particular the regulatory approach of the U.S. Securities and Exchange Commission (SEC) and the approach of the Financial Stability Board (FSB) based on the reference asset category. On the basis of their critical analysis, the author proposes a multidimensional classification of tokens according to six criteria: functional purpose, role in decentralized finance, method of collateralization, nature of issuance, fungibility, and jurisdictional characteristic. The microeconomic effects of asset tokenization are systematized, encompassing five interrelated groups: structural effects (fractionalization of property rights, disintermediation, formation of new market structures), transactional and price effects (reduction of transaction costs, improvement of asset liquidity), behavioral effects (transformation of incentives and decision-making patterns of economic agents), market equilibrium effects (expansion of supply and demand), and network effects (economies of scale, risks of market fragmentation). It is established that these effects are interconnected and collectively form a new microeconomic environment for the functioning of financial markets.

Sivamurugan Perumal

Blockchain Technology is a Distributed Ledger Technology (DLT) where the data (digital information) is stored in multiple computers and not in a centralized one [1]. Each system would store a copy of the distributed ledger to avoid pitfalls. The information persists as blocks and gets updated simultaneously on all environments after being validated. Four main types of Blockchain, as described: private/permissioned, public/permissionless, hybrid, and consortium [2]. Corda is an open-source platform of a distributed ledger founded by R3 Consortium (R3CEV LLC). DLT is based on peer-to-peer connections with an agreement, and it is not part of the public. Corda architecture is non-native to cryptocurrencies. The platform is based on top of the Java Virtual Machine (JVM), written in Kotlin. Overall, it explains how Corda can be implemented in a wide range of industries with private/permissioned networks. Earlier, blockchain technology was public and permissionless, which posed a little challenge to many industries to adapt, even in the Supply Chain Management system (SCM) and healthcare. Corda is an open-source and DLT concept with private and permissioned features that make it easy to use in industries like SCM, and how that can be achieved.

Ibrahim Abdou Zabeye, Zakari Aboubacar

The current research is about the financing of school participatory structures, particularly FC / CGDES and CGDES in the commune of Droum, Niger Republic. It essentially aims at determining the explanatory factors of financial gap of these structures that are partnership frameworks between the State, development partners, schools, families and community. To do this, both qualitative and quantitative data have been collected across the questionnaire, the snowball technique, the direct observation. Our analyzes showed the existence of factors which created a financial lack directly hindering the achievement of activities of these structures within schools. Added to this, are internal and external parameters including the reluctance of parents linked to their bad connotation of school of white, local actors strategies of co-optation, etc. The whole of these factors determined the low mobilization of funds for the financing of these structures in Droum.

Ndumiso Zondi, Stacey Baror, Sheunesu Makura, Hein Venter

Centralised digital identity management systems create single points of failure and weaken user control over sensitive data, particularly in financial services. We designed and built RandX, an ERC-20 token that gates mint, transfer, and burn operations to addresses with verifiable credentials. Requirements drawn from self-sovereign identity (SSI) and AML/KYC literature led to a modular architecture for identity, user management, token logic, and governance. Solidity contracts were implemented with a React/MetaMask dApp. End-to-end tests confirm verified users transact successfully while unverified attempts revert. Average gas costs were approximately 0.0008 ETH per token operation and 0.0014 ETH for identity verification. We note issuer centrality and propose multisig governance and zero-knowledge proofs as next steps.

Febriana Nur Aini, Manda Fatimah Azaziah, Muhammada Rifki Iqbal Ghufron, Muhammad Dava Khoirur Roziqy · 5 authors

Penyimpanan informasi sensitif pada aplikasi catatan digital menimbulkan tantangan terkait keamanan dan privasi data pengguna. Sebagian besar sistem penyimpanan konvensional masih memberikan akses terhadap data yang disimpan pada sisi backend, sehingga meningkatkan risiko kebocoran informasi apabila terjadi kompromi sistem. Penelitian ini bertujuan untuk merancang dan mengimplementasikan aplikasi web Secret Ink dengan mengintegrasikan algoritma Advanced Encryption Standard (AES) 256-bit dan prinsip Zero-Knowledge sebagai mekanisme perlindungan data. Metode penelitian yang digunakan meliputi analisis kebutuhan, perancangan arsitektur keamanan, implementasi sistem menggunakan teknologi berbasis JavaScript, serta pengujian fungsionalitas dan keamanan aplikasi. Hasil penelitian menunjukkan bahwa proses enkripsi dan dekripsi dapat dilakukan pada sisi pengguna, sementara backend hanya menerima dan menyimpan data dalam bentuk ciphertext. Pengujian keamanan juga menunjukkan bahwa sistem mampu memitigasi ancaman umum aplikasi web, seperti Cross-Site Request Forgery (CSRF), Cross-Site Scripting (XSS), dan SQL Injection. Dengan demikian, Secret Ink berhasil menyediakan mekanisme penyimpanan catatan digital yang mampu menjaga kerahasiaan dan privasi data pengguna melalui penerapan AES-256 dan arsitektur Zero-Knowledge

Mays Munqith Salman, Mohammed Falih AL-Gailani

No abstract is available for this record.

Assignee Research

This report synthesises findings from 8 peer-reviewed papers addressing the following research question: How does communication efficiency in federated learning for code generation models scale with model size and client heterogeneity relative to centralized distributed training approaches. Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decentralized. FL embodies. 10 claims were extracted from source literature; 10 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.7/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: How does communication efficiency in federated learning for code generation models scale with model size and client heterogeneity relative to centralized distributed training approaches? Autonomous literature synthesis. Automated review score: 8.7/10. Full text and citation available at Assignee Research.

Assignee Research

This report synthesises findings from 8 peer-reviewed papers addressing the following research question: Does the stochastic control variate approach in WAFFLE improve inference efficiency and reduce latency variance in personalized multimodal models compared to standard FedAvg under straggler conditions. Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decentralized. FL embodies. 10 claims were extracted from source literature; 9 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.7/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: Does the stochastic control variate approach in WAFFLE improve inference efficiency and reduce latency variance in personalized multimodal models compared to standard FedAvg under straggler conditions? Autonomous literature synthesis. Automated review score: 7.7/10. Full text and citation available at Assignee Research.