Blockchain Papers

Yuting Xu, Lin Chen, Yue Xiang, Kui Liu

No abstract is available for this record.

Oyovwe Akajagbor, Ofuan James Ilaboya

No abstract is available for this record.

Nicola Dimitri

No abstract is available for this record.

Rui Qin, Xiao Xue, Yong Yuan, Xiaolong Liang

In decentralized governance, existing token-based voting mechanisms employed by Decentralized Autonomous Organizations (DAOs) often suffer from centralization risks, as a small number of large token holders can dominate decision-making. While reputation-based voting has emerged as an alternative that reflects members’ historical contributions, it is also prone to ossification, where early contributors accumulate disproportionate influence over time. To address these challenges, we propose a novel hybrid dynamic voting mechanism that combines tokens and reputation in the voting power. Furthermore, we incorporate an exponential decay mechanism into the reputation component to ensure that voting power dynamically reflects recent and active participation rather than legacy status. We also utilize Gini and Nakamoto coefficients to evaluate the proposed mechanism. To validate our proposed mechanism, we design some computational experiments, and the experimental results show that the proposed hybrid mechanism achieves better fairness and decentralization, while allowing new contributors to more quickly gain meaningful influence. This work provides insights into designing adaptive, fair, and secure governance mechanisms for DAOs.

Mario A. Cypko, Charan Annadurai, Dominik Welte, Aditya Kumar · 6 authors

Abstract—The secure and controlled access to medical data is a critical challenge in modern clinical research. Regulatory frameworks such as the GDPR and the EU AI Act impose strict requirements on data access, privacy, and transparency, making conventional data-sharing processes inefficient and administratively burdensome. Our proposed HyperAccess platform aims to digitise and streamline the contractual access management of medical data through Hyperledger Fabric, an enterprise-grade, permissioned blockchain framework. The project introduces a semi-automated access control system that minimizes administrative efforts while maximizing trust among stakeholders, including data holders, data owners, and data users. By employing exclusive channels on Hyperledger Fabric, only stakeholders involved in an agreement are part of the dedicated channel. This paper presents the design principles, technological framework, and potential impact of HyperAccess on multicentre clinical research, offering a scalable, privacypreserving, and practically validated solution through an initial prototypical implementation.

Sergii Grybniak, О. Д. Кічмаренко, Yevhen Leonchyk, Igor Mazurok · 6 authors

No abstract is available for this record.

Wieland Müller

The dissertation explores theoretical and practical implications of smart contracts in supply chains through four studies. It examines technology adoption, trust dynamics, transaction costs, and applications in virtual supply networks. Building on literature and empirical data, the work highlights both opportunities and challenges of this technology and provides actionable insights for practitioners as well as contributions to advancing existing theoretical frameworks.

Chuxuan Fan, Tao Shu, Fei Xie

No abstract is available for this record.

Qinxu Ding, Weibiao Xu, Zhiguo Wang

No abstract is available for this record.

Fan Zhou

Decentralized finance (DeFi) is the concept of building financial infrastructures without relying on centralized intermediaries. A notable development in DeFi is the creation of decentralized exchanges (DEXs), which operate as smart contracts on a blockchain. Due to the high cost of on-chain operations, automated market makers (AMMs) such as Uniswap v3 have emerged as the prevailing model of liquidity provision on DEXs. Two closely related research questions arise in the DeFi space: (1) What are the optimal strategies of liquidity providers given an AMM design such as Uniswap v3? (2) How should the design of AMMs be optimized to achieve objectives such as profit maximization? This thesis addresses these two central research questions using computational methods, in particular, through differentiable optimization. Chapters 2 and 3 study the optimal strategies of liquidity providers (LPs) in Uniswap v3. In both chapters' formulations, the expected utility of an LP is differentiable with respect to its liquidity allocation under any exogenous price sequence, enabling differentiable optimization of LP strategies. With the formulation of a convex stochastic optimization problem that can be solved in a differentiable manner, Chapter 2 explores optimal static LP strategies in economic settings with varying factors such as an LP's belief about price dynamics, risk aversion, and for different specifications of the Uniswap v3 liquidity pool. Understanding LP strategies also leads to insights into the design of Uniswap v3 liquidity pools. Under a similar optimization framework, Chapter 3 extends from static LP strategies to dynamic LP strategies, specifically LP strategies that reallocate liquidity whenever the price movement reaches a certain threshold. These proposed dynamic strategies—particularly context-dependent variants modeled by a neural network, which adapt the shape of liquidity allocation to contextual information such as price and moving average of non-arbitrage trade volume at the time of reallocation—are shown to lead to significant gains compared to static LP strategies. Taking a broader perspective on AMM design, Chapter 4 optimizes market-making mechanisms for a single trade in settings with multiple traded goods, seeking market maker profit maximization under adverse selection. Conjectures of optimal mechanisms are generated using tools of differentiable economics, which uses differentiable optimization for economic design. To prove the optimality of proposed mechanisms, a duality theorem is established between the market-making mechanism design problem and an optimal transport problem. This approach of combining differentiable economics with theoretical analysis is used to develop a parameterized class of optimal market-making mechanisms. These results also establish that, in some cases, the optimal market maker across multiple goods must use complex bundling. Additional conjectures about the structure of optimal mechanisms are presented, and an empirical optimality bound is established for some conjectures by approximately solving the dual with linear programming. The second part of this thesis studies transfer learning of the Gaussian process (GP) prior in Bayesian optimization (BO), a widely used black-box function optimization method. Previous GP-based transfer learning methods for BO are limited to utilizing historical data collected from black-box functions with the same domain as the new black-box function to be optimized. The proposed method, model pre-training on heterogeneous domains (MPHD), employs a neural network that maps from domain-specific contextual information to specifications of hierarchical GPs for a given domain. As a result, MPHD is able to transfer knowledge across heterogeneous domains such as hyperparameter-tuning for different machine learning models. It is shown through theoretical analysis and empirical results that MPHD is a practical transfer learning method for BO, with demonstrations of competitive performance on challenging real-world hyperparameter-tuning tasks.

Eric Alston, Bryce Bugge, William Lehr

No abstract is available for this record.

Chuki Hayama, Yoko Kamidoi, Masataka Kawasaki, Shin’ichi Wakabayashi

Cryptocurrencies are based on blockchains that are distributed ledgers for recording transactions. In 2024, these had a value of more than $3.70 Trillion in market capitalization. Ethereum is one of the most representative cryptocurrencies and dominates approximately 10% of total cryptoassets in 2025. The Ethereum blockchain system includes two types of account; contract accounts (CAs) and externally owned accounts (EOAs). We focus on the unilateral sending of cryptocurrencies to CAs and EOAs on Ethereum blockchain. We call this unilateral sending of cryptocurrencies without the recipient’s awareness, the recipient’s unapproved transactions. If the sender were malicious or criminal, the recipient of the unilateral sending might have been involved in some crime. In this paper, we provide two protection methods for CAs and EOAs on the Ethereum blockchain system and combine the two methods into a two-phase receipt mechanism for recipients to selectively reject unilateral sending of cryptocurrencies. We introduced and implemented this mechanism on open-source software for Ethereum developers, called Truffle Suite, and then executed experiments on a personal Ethereum blockchain called Ganache, provided by Truffle Suite. The experimental results demonstrated that the overhead of introducing the mechanism is reasonable at a few US dollars.

Daniel Liebau

No abstract is available for this record.

Wulf A. Kaal

No abstract is available for this record.

Cristiano Bellavitis, Paul P. Momtaz

Decentralized autonomous organizations (DAOs) crowdfunds to invest in various projects. The decentralization feature of DAOs submits that decision-making is a collective democratic action of all DAO members. The autonomy feature of DAOs suggests that decision-making is an algorithmic process governed by self-executing smart contracts. However, in reality, DAOs are neither perfectly decentralized nor completely autonomous. Our empirical analysis shows that deviations from the ideals of decentralization and autonomy are costly. Non-algorithmic off-chain voting governance of decision-making leads to a substantial discount in DAO value. Non-decentralized aspects such as large voting coalitions also affect DAO value. Interaction effects are also shown. The study implies that platform governance design choices are crucial for DAO success. • DAOs with off-chain voting raise 87% less funding. • Larger communities worsen the valuation hit from off-chain voting. • Big voting coalitions deepen off-chain governance drawbacks. • On-chain transparency is key to DAO success—especially in large technical teams.

Lennart Ante

This paper investigates the intersection of artificial intelligence (AI) agents—autonomous software entities capable of adapting, learning, and executing multi-step operations—and decentralized finance (DeFi) ecosystems. It highlights how the adaptive decision-making capabilities, flexible governance frameworks, and data-driven optimization strategies of AI agents reshape market coordination and organizational architectures. Drawing on a qualitative analysis of 306 major crypto AI agents, the study introduces a typology that maps their diverse application areas, including algorithmic trading, portfolio management, sentiment-driven communities, and immersive entertainment. To further conceptualize the role of AI in decentralized governance, the paper develops a quadrant-based framework that distinguishes four archetypal system configurations: Traditional Decentralized Autonomous Organization (DAO) Tools, Maximally Distributed Agency, Closed Systems, and AI Dictatorships. These configurations, defined by varying degrees of autonomy and decentralization, reveal critical trade-offs between transparency, efficiency, adaptability, and control. This framework serves as a lens to theorize how AI agents reconfigure trust mechanisms, power dynamics, and decision-making processes in decentralized ecosystems. Grounded in economic and socio-technical theory, the paper positions AI agents as transformative intermediaries in tokenized environments. While demonstrating their capacity to streamline operations, enhance decision quality, and enrich user engagement, the study also addresses the governance risks posed by algorithmic control and systemic opacity. Taken together, the conceptual and empirical insights lay a foundation for ongoing interdisciplinary inquiry into the evolving role of AI agents in decentralized finance. • Introduces a typology of 306 AI agents across key DeFi application areas • Maps AI agent roles in trading, governance, community, and entertainment • Develops a governance framework for AI agent autonomy and decentralization • Shows how AI agents reduce transaction costs and reshape market structures • Highlights risks of opacity, misalignment, and centralization in DeFi AI use

Asnaf Ahmad, Hamza Mehmood

Financial industry operations have been substantially reformed through the adoption of decentralized applications (dApps) as well as blockchain technology during recent years. This research aims to handle three main issues within decentralised finance (DeFi) by focusing on transaction functionality execution and system scalability and enhanced security features. We implemented secure measures for integer overflows and reentrancy avoidance through extensive testing which proved successful in eliminating reentrancy gaps and integer overflows. The scalability tests demonstrated functioning performance with network congestion but bigger congestion caused noticeable delays alongside elevated latency levels. Due to the nature of large transaction processing additional optimization measures need implementation. The results of functional testing showed that 100% of token transfers succeeded together with 97.5% success rate for asset management operations. The success rate of decentralized trade operations reached 96% according to results. Smart contract implementations succeed in protecting transactions yet need additional work to increase scalability and improve decentralized exchange functions. The research concludes that smart contract-based DeFi solutions show substantial promise yet demands continuous advancement to gain more widespread market adoption.

S Chen

Currently, the advantages of Shapley value in explaining model decisions have made incentive mechanisms Shapley value contribution assessment based become major research focus. This approach ensures the effectiveness and fairness of contribution assessment algorithms. However, there is a significant issue regarding the reliability of the computational results. Additionally, traditional Shapley value-based contribution processes face an issue where computational complexity increases exponentially with the number of participants. Addressing these issues, this paper proposes a contribution assessment and reward framework based on Shapley value and smart contract technology using alliance blockchain. This framework overcomes the reliance on third-party institutions that is characterized by traditional incentive mechanisms, leveraging the decentralized nature of blockchain to eliminate trust issues associated with a single centralized entity. Furthermore, the traceability of blockchain ensures the transparency and traceability of the contribution assessment and reward distribution processes.

Fatou Ndiaye Mbodji, Boladji Vinny Adjibi, M. Diouf, Gervais Mendy · 7 authors

Due to the inherent immutability of blockchain technology, smart contract updates require their deployment at new addresses rather than modifying existing ones, thus fragmenting version histories and creating critical blind spots for analyses. Indeed, for example, this fragmentation severely hinders security researchers ability to track vulnerability lifecycles across contract versions. While platforms like Etherscan provide detailed information about Ethereum smart contracts, they lack crucial functionality to trace predecessor-successor relationships within smart contract lineages, preventing systematic analysis of how vulnerabilities emerge, propagate, and potentially remain unresolved across versions.To address the challenge of tracing smart contract lineages, we adopt a Design Science Research (DSR) approach and introduce ContractTrace, an automated infrastructure that accurately identifies and links versions of smart contracts into coherent lineages. This tool enables the construction of lineageSet, an up-to-date, open-source dataset specifically designed to support security research on vulnerability, defect or any other property evolution patterns in smart contracts. Through a security-focused case study we demonstrate how ContractTrace reveals previously obscured vulnerability life-cycles within smart contract lineages, tracking whether critical security flaws persist or get resolved across versions. This capability is essential for understanding vulnerability propagation patterns and evaluating the effectiveness of security patches in blockchain environments. In the evaluation phase of our DSR approach, we validated our lineage detection methodology against an alternative approach using Locality-Sensitive Hashing (LSH) to cluster contract versions, confirming the security relevance and accuracy of our technique.

Seungwon Jeong

In the Delegated Proof-of-Stake blockchain, block producers (BP) are elected by stake-weighted vote. The supermajority of BPs can change the rule of the blockchain; thus, preventing the centralization of votes is important. We find the optimal number of votes per account (VPA) that minimizes takeover risks while maximizing voting flexibility. A smaller VPA requires more stake for takeover, but only up to a certain point, implying that the ‘one vote per account’ rule adopted by some major blockchains to mitigate centralization may be unnecessary. Our results are applicable to any environments in which multiple decision makers are elected by voting.

Fei Wu, Thomas Thiery, Stefanos Leonardos, Carmine Ventre

Block production on the Ethereum blockchain has adopted an auction-based mechanism known as Proposer--Builder Separation (PBS), where validators outsource block creation to builders competing in MEV--Boost auctions for Maximal Extractable Value (MEV) rewards. We employ empirical game-theoretic analysis based on simulations to examine how advantages in latency and MEV access shape builder strategic bidding and auction outcomes. We find that a small set of dominant builders leverage these advantages, consolidating power, reducing auction efficiency, and heightening centralization. Our results underscore the need for fair MEV distribution and sustained efforts to promote decentralization in Ethereum's block building market.

Adwaita Raj Modak, K. Niha, P. Swarnalatha, Gandhi Kishor Addanki

Blockchain technology introduces decentralized and immutable ledgers that provide trust and transparency in data management whereas smart contracts can automate business processes. Accessing, and querying data stored on blockchain networks can be challenging due to their complex data structures and limited querying capabilities. In this chapter, we will enhance smart contract-enabled chains' functionality by developing a decentralized database and distributed indexer system capable of executing SQL-like queries on blockchain data. GunDB, a decentralized database known for its robustness and flexibility, enables efficient and simplified data retrieval from blockchain networks. By integrating this database with smart contract-enabled chains, we bridge the gap between blockchain technology and traditional querying methodologies, enabling developers and users to access blockchain data using Structure Query Language-like syntax. Through a carefully designed indexing process, we ensure that the data is efficiently indexed and retrieved with security and immutability characteristics.

Jianwei Liu, Wei Wan, Chun Long, Jing Li · 6 authors

In zero-trust environments, fair exchange schemes have long faced challenges of low efficiency and high computational overhead when verifying the integrity of large-scale data. To address these issues, this paper proposes ZKFDT, an efficient data fair exchange scheme based on optimized zero-knowledge proof algorithms, offering improvements in efficiency, fairness, and security. In terms of efficiency, ZKFDT leverages IPFS’s hash-based addressing mechanism to significantly reduce network communication overhead compared to traditional data transmission methods, while also optimizing the multi-scalar multiplication algorithm, improving proof generation efficiency by 2x. Regarding security, ZKFDT adopts the more secure ABR23 protocol, addressing the malleability attack vulnerabilities of Groth16 while maintaining its low communication overhead. Through the implementation of smart contracts, including proof verification, atomic swaps, and time-lock functionality, ZKFDT ensures fairness and immutability in data transactions. Experimental results show that ZKFDT demonstrates high efficiency and practical feasibility in large-scale data transaction applications.

Yixuan Fan, Ziyi Zhou, Zhixiang Qiao, Yao Sun · 5 authors

Decentralized autonomous organizations (DAOs), originating from Ethereum, are pioneering entities in the world of Web 3, driven by the decentralization philosophy. In DAO systems, voting mechanisms are essential for decision-making. Their design is crucial for both community development and individual interest protection. While research has explored critical aspects such as decentralization, security, and effectiveness, there is a noticeable absence in analyzing the efficiency of DAO voting mechanisms. To address this, we focus on three key efficiency factors in DAO voting: voter turnout, processing time, and accuracy. Specifically, we identify high voter participation, shorter voting periods, and an approximately neutral approval rate as the primary factors for an efficient DAO voting process. Using a stochastic process model for DAO voting, we explore the interrelationship between these factors. We observe a trade-off between a shorter voting period and an approval rate closer to neutrality, and we also find a positive relationship between increased voter participation and achieving an appropriate approval rate. Finally, in simulations, we examine four common DAO voting mechanisms to determine their most efficient ranges.