Blockchain Papers

Е.И. Дюдикова

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Chenyang Peng, Haijun Wang, Wu Yin, Hao Wu · 7 authors

With the advance application of blockchain technology in various fields, ensuring the security and stability of smart contracts has emerged as a critical challenge. Current security analysis methodologies in vulnerability detection can be categorized into static analysis and dynamic analysis methods.However, these existing traditional vulnerability detection methods predominantly rely on analyzing original contract code, not all smart contracts provide accessible code.We present ETrace, a novel event-driven vulnerability detection framework for smart contracts, which uniquely identifies potential vulnerabilities through LLM-powered trace analysis without requiring source code access. By extracting fine-grained event sequences from transaction logs, the framework leverages Large Language Models (LLMs) as adaptive semantic interpreters to reconstruct event analysis through chain-of-thought reasoning. ETrace implements pattern-matching to establish causal links between transaction behavior patterns and known attack behaviors. Furthermore, we validate the effectiveness of ETrace through preliminary experimental results.

Herman Zahid, Adil Zulfiqar, Muhammad Adnan, Muhammad Sajid Iqbal · 7 authors

This review explores the transformative architecture of Smart Grid 3.0 by integrating cutting-edge technologies. It presents novel architectural frameworks to transform nanogrid, microgrid, and VPP topologies to their Grid 3.0 counterparts. This study systematically analyzes the application of advanced algorithms and technologies across all hierarchical subsystems—nanogrid 3.0, microgrid 3.0, VPP 3.0, and Smart Grid 3.0. These digital technologies have transformative capabilities. The digital twins can perform real-time monitoring, simulation, and predictive analysis; blockchain ensures secure, decentralized energy transactions; and the metaverse creates immersive, interactive environments for system management. This review also explores the role of AI in power grid which is to optimize energy scheduling, fault detection, and energy management. This paper adds to the literature by systematically addressing subsystems of Smart Grid 3.0, including energy generation, transmission, distribution, communication, and storage. Challenges such as interoperability, scalability, data integrity, and cybersecurity are discussed, and solutions are proposed which highlights the need of interdisciplinary approach. These include cyber-attack detection and mitigation mechanisms, advanced simulation tools, and robust policy frameworks. A thorough review of literature enabled this paper to present practical implementation strategies and real-world examples of digital technologies integrated smart grids. By integrating these technologies across hierarchical energy systems, this study establishes a foundation for future research in transforming conventional smart grid infrastructure into a resilient, efficient, and interconnected cyber-physical energy network called Smart Grid 3.0 as the peak of this evolution so far.

Marvin Hanisch, Curtis Goldsby, Mélissa Fortin, Michael Rogerson

ABSTRACT Blockchain‐based platforms can facilitate data sharing and coordination in interorganizational ecosystems by enabling secure, tamper‐evident recordkeeping and streamlined, trust‐minimized transactions across organizational boundaries. However, their decentralized architecture may conflict with the centralized control exercised by platform sponsors, giving rise to a centralization–decentralization paradox. This study explores how this paradox unfolds in a large, blockchain‐based logistics platform that was ultimately discontinued. Through an in‐depth, longitudinal case study, we identify three interrelated governance contradictions—regarding ownership, trust, and growth—that triggered destabilizing oscillations between centralized and decentralized governance modes. We introduce the concept of semirigid limits to capture the bounded flexibility within which governance can be made and adapted under such paradoxical conditions. Our findings show that the centralization–decentralization paradox is especially difficult to navigate when strategic boundary conditions—here, industry competition, fragmented coordination, and high interdependencies—are present. Our study contributes to the paradox and governance literature by theorizing how governance contradictions emerge and persist and by identifying the mechanisms that constrain alignment and adaptation. We also offer guidance for managers in regard to addressing the competing demands of centralization and decentralization in interorganizational platforms.

Ranjit Kannappan, Julien Hatin, E. Bertin, Noël Crespi

The Digital Product Passport (DPP) is a key enabler of the European Union’s vision for a circular economy. Achieving the full potential of DPP requires addressing the challenges of traditional product lifecycle systems (PLM). Traditional PLM focuses on streamlining data management and decision making. However, their centralized architecture limits transparent, crossorganizational collaboration, impacting the circular economy efforts. This paper proposes a blockchain based framework, tailored to support DPP implementation by enabling the creation and sharing of lifecycle data using digital twin technology. The proposed architecture implements two types of digital twins - Component Digital Twin and Product Digital Twin modeled using the Asset Administration Shell (AAS) standard to ensure interoperability. The architecture leverages Ethereum smart contracts for blockchain interaction and IPFS for off-chain decentralized storage. Two approaches for secure data sharing are implemented: Direct and Signature-based data sharing. Performance evaluation shows low latency for key operations like twin creation (167 ms) and data sharing (64 ms). By leveraging decentralization in DPPs, the proposed framework fosters collaboration, transparency, and circular economy practices, empowering stakeholders to access and share critical product data throughout the lifecycle.

Yuki Mahardhito Adhitya Wardhana, Elvira Yoanita, Dwita Sutjiningsih

Access to safe drinking water remains a pressing global issue, with over 2.2 billion people still lacking safely managed water services. In Indonesia, rural communities often face disparities in access, relying on decentralized systems with limited sustainability. This study investigates financing mechanisms for community-based rural water utilities (RWS) in Piyungan Subdistrict, Bantul Regency, to identify suitable models that support long-term service sustainability. By employing Analytical Hierarchy Process (AHP) method, this research analyzes social, economic, and environmental criteria and sub-criteria influencing financing preferences from the RWS. Primary data were collected through structured interviews and questionnaires with eight RWS entities meeting specific performance and operational criteria. The results show that social factors, particularly community-based management and participation, are the most influential in sustaining RWS. Among four financing alternatives, community financing emerged as the most preferred (62%), followed by private financing and grants, with debt financing receiving the lowest priority. These findings highlight the critical role of local engagement, institutional capacity, and adaptive financial strategies in ensuring service continuity. The study proposes a phased, blended financing approach, tailored to each stage of RWS development, emphasizing that long-term sustainability must be supported by institutional reforms, improved financial management, and environmental risk governance.

A. V. Fedorov

The financial system of sub-Saharan Africa is heavily dependent on foreign and international capital. The external debt of Sub-Saharan Africa is more than 60% of the total GDP, in some countries, that is about 95%. In the last decades, there has been an expansion of the influence of pan-African financial groups and central/national banks in the monetary policy of African states. Sub-Saharan Africa shows exponential growth in electronic mobile payments and the digital currency of central banks and crypto assets depends on distributed ledger technology. Regional financial centers have emerged, shaping the growth and development of African finance. The structure, specifics and main trends in the development of the financial system of sub-Saharan Africa are described in the context of the challenges facing the global financial system. The need for integration processes for the countries of the continent, the role of central banks and Pan-African financial institutions are substantiated. The possibility of implementing the concept of leapfrogging in the transition of the monetary and credit system of the African continent to national digital currencies and the use of distributed register technology are considered. The author considers the credit and monetary system of Sub-Saharan Africa as a place of financial innovations that can identify the development of the global financial system for decades to come.

Zaheda Daruwala

Cryptocurrencies have experienced exponential growth within the last decade, with market capitalization hovering above the one-trillion-dollar mark since 2022. One area of concern for current and potential crypto users and investors is their unprecedented price volatility. As cryptos become interlinked with the regulated financial system, questions emerge regarding the possibility of linkages of their prices to the external environments. Financial and macroeconomic factors of inflation, economic growth, interest rates, currency exchange rates, equity market returns, corporate bond yields, gold and oil prices are examined against the cryptocurrency returns. This study encompasses a multi-analytical approach, firstly with the empirical tests of Spearman’s correlational analysis to discover the most pertinent relationships, followed by the PCA analysis to reduce redundancy. The predictive regression model of the Granger Causality test, a vector autoregression (VAR) time series forecasting method, is applied to examine whether the highly effective factors Granger cause the crypto price movements. The Machine Learning Random Forest Regression is also applied where a nuanced understanding of the external factors affecting cryptos prices is gained. The findings of this study pertain to more recent times when the pandemic crisis has subsided and stable economies are in place. The results examined four major cryptos of Bitcoin, Binance Coin, Ripple and Tether, where most behaviours suggest that users and investors are willing to take on riskier assets during periods of economic growth, a strong equity market complements crypto demands and gold and oil are good substitutes for cryptos. Tether, a stablecoin, was the least impacted by external factors and behaved similarly to a fiat currency. This investigation into external factors will empower cryptocurrency users and investors with valuable insights into the crypto price mechanisms, enabling them to refine their investing and portfolio diversification strategies.

Massimo Bartoletti, E. Lipparini

Lending protocols are one of the main applications of Decentralized Finance (DeFi), enabling crypto-assets loan markets with a total value estimated in the tens of billions of dollars. Unlike traditional lending systems, these protocols operate without relying on trusted authorities or off-chain enforcement mechanisms. To achieve key economic goals such as stability of the loan market, they devise instead trustless on-chain mechanisms, such as rewarding liquidators who repay the loans of under-collateralized borrowers by awarding them part of the borrower's collateral. The complexity of these incentive mechanisms, combined with their entanglement in low-level implementation details, makes it challenging to precisely assess the structural and economic properties of lending protocols, as well as to analyze user strategies and attacks. Crucially, since participation is open to anyone, any weaknesses in the incentive mechanism may give rise to unintended emergent behaviours, or even enable adversarial strategies aimed at making profits to the detriment of legit users, or at undermining the stability of the protocol. In this work, we propose a formal model of lending protocols that captures the essential features of mainstream platforms, enabling us to identify and prove key properties related to their economic and strategic dynamics.

Wei Kuang

The environmental concerns associated with energy-intensive cryptocurrencies have led to the rise of clean cryptocurrencies, which aim to balance financial innovation and sustainability. This study investigates whether clean cryptocurrencies improve portfolio resilience while promoting environmental goals in the cryptocurrency market. Using dynamic correlation-based hedge and safe-haven regression models, relative risk ratio analysis with higher-order moments risks, and multiple portfolio optimization strategies, we assess the impact of integrating clean cryptocurrencies into portfolios composed mainly of traditional cryptocurrencies. The results show that clean cryptocurrencies consistently reduce tail risk during periods of market stress; however, this risk reduction does not always result in higher returns or better risk-adjusted performance. These findings have important implications for both investors and policymakers. Clean cryptocurrencies can help investors manage tail risk and align with ESG goals, but their implementation requires a careful assessment of return expectations and investment constraints. Policymakers are encouraged to create a regulatory framework that fosters sustainable digital asset development while protecting investors and ensuring market stability. This study contributes to a deeper understanding of clean cryptocurrencies’ role in sustainable investment strategies within the evolving digital asset landscape.

Flavien Dermigny, Vania Conan, Samia Bouzefrane, Pengwenlong Gu · 6 authors

In the domain of authentication, information leakage which can lead to identity theft represents a significant challenge in the field of cybersecurity. This challenge is particularly relevant in the context of 5 G tactical bubbles, where secure and efficient authentication mechanisms are critical to gain access to sensitive information and communication services. The concept of Zero-Knowledge Proofs, in particular non-interactive proofs, has gained attention in recent years as robust cryptographic methods for privacy-preserving protocols. Zero-knowledge proofs enable users to prove possession of specific knowledge to verifiers without revealing the knowledge itself in a single interaction round. Despite its growing popularity, Zero-Knowledge Proofs have not yet been fully explored within 5 G tactical bubbles. In this paper, we perform a comparative analysis between traditional authentication mechanisms and Zero-Knowledge Proofs-enabled authentications. To this end, we evaluate the feasibility in terms of time and computational complexity and determine whether these advanced authentication protocols can ensure enhanced privacy and security in 5 G tactical bubbles.

Majid Khabbazian

The Fair Data Exchange (FDE) protocol (CCS'24) achieves atomic, pay-per-file exchange with a constant on-chain footprint, but existing implementations do not scale: proof verification can take hours even for files of only tens of megabytes. In this work, we present two FDE implementations: VECKplus and VECKstar. VECKplus reduces client-side verification to O(lambda) -- independent of file size -- where lambda is the security parameter. VECKplus brings verification time to approximately 1 s on a commodity desktop for any file size. VECKplus also significantly reduces proof generation time by limiting expensive range proofs to a Theta(lambda)-sized subset of the file. This improvement is especially beneficial for large files, even though proof generation and encryption are already precomputable and highly parallelizable on the server: for a 32 MiB file, for instance, proof generation time drops from approximately 6,295 s to approximately 4.8 s (approximately 1,300x speed-up). As in the existing ElGamal implementation, however, VECKplus retains exponential ElGamal over the full file. Consequently, the client must perform ElGamal decryption and download ciphertexts that are at least 10x the plaintext size. We address both drawbacks in the second implementation, VECKstar: we replace bulk ElGamal encryption with a fast, hash-derived mask and confine public-key work to a Theta(lambda) sample tied together with a file-size-independent zk-SNARK, adding less than 0.1 s to verification in our prototype. Importantly, this also reduces the communication overhead from at least 10x to less than 50%. Together, these changes yield plaintext-scale performance. Finally, we bridge Bitcoin's secp256k1 and BLS12-381 with a file-size-independent zk-SNARK to run FDE fully off-chain over the Lightning Network, reducing fees from approximately USD 10 to less than USD 0.01 and payment latency to a few seconds.

Julia Kończal

The cryptocurrency options market is notable for its high volatility and lower liquidity compared to traditional markets. These characteristics introduce significant challenges to traditional option pricing methodologies. Addressing these complexities requires advanced models that can effectively capture the dynamics of the market. We explore which option pricing models are most effective in valuing cryptocurrency options. Specifically, we calibrate and evaluate the performance of the Black-Scholes, Merton Jump Diffusion, Variance Gamma, Kou, Heston, and Bates models. Our analysis focuses on pricing vanilla options on futures contracts for Bitcoin (BTC) and Ether (ETH). We find that the Black-Scholes model exhibits the highest pricing errors. In contrast, the Kou and Bates models achieve the lowest errors, with the Kou model performing the best for the BTC options and the Bates model for ETH options. The results highlight the importance of incorporating jumps and stochastic volatility into pricing models to better reflect the behavior of these assets.

Amrit Poudel, Yifan Ding, Jurgen Pfeffer, Tim Weninger

Search engines play a crucial role as digital gatekeepers, shaping the visibility of Web and social media content through algorithmic curation. This study investigates how search engines like Google selectively promotes or suppresses certain hashtags and subreddits, impacting the information users encounter. By comparing search engine results with nonsampled data from Reddit and Twitter/X, we reveal systematic biases in content visibility. Google's algorithms tend to suppress subreddits and hashtags related to sexually explicit material, conspiracy theories, advertisements, and cryptocurrencies, while promoting content associated with higher engagement. These findings suggest that Google's gatekeeping practices influence public discourse by curating the social media narratives available to users.

Cui Zhang, Maoxin Ji, Qiong Wu, Pingyi Fan · 5 authors

As Internet of Vehicles (IoV) technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to malicious external attacks, resulting in information loss or even tampering, thereby creating serious security vulnerabilities. Blockchain technology can maintain a shared ledger among servers. In the Raft consensus mechanism, as long as more than half of the nodes remain operational, the system will not collapse, effectively maintaining the system's robustness and security. To protect vehicle information, we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing. To address the additional latency introduced by blockchain, we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency, ensuring that the system meets the requirements for low latency and high reliability. Simulation results demonstrate that the optimized data extraction rate significantly reduces system delay, with relatively stable variations in latency. Moreover, the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments, such as 5G and next-generation smart city systems.

Dr Craig S Wright

This paper formally examines the network structure of Bitcoin CORE (BTC) and Bitcoin Satoshi Vision (BSV) using complex graph theory to demonstrate that home-hosted full nodes are incapable of participating in or influencing the propagation topology. Leveraging established models such as scale-free networks and small-world connectivity, we demonstrate that the propagation graph is dominated by a densely interconnected miner clique, while full nodes reside on the periphery, excluded from all transaction-to-block inclusion paths. Using simulation-backed metrics and eigenvalue centrality analysis, we confirm that full nodes are neither critical nor operationally relevant for consensus propagation.

Zhong Yang, Zhengqiu Zhu, Yong Zhao, Yonglin Tian · 19 authors

Underwater target tracking technology plays a pivotal role in marine resource exploration, environmental monitoring, and national defense security. Given that acoustic waves represent an effective medium for long-distance transmission in aquatic environments, underwater acoustic target tracking has become a prominent research area of underwater communications and networking. Existing literature reviews often offer a narrow perspective or inadequately address the paradigm shifts driven by emerging technologies like deep learning and reinforcement learning. To address these gaps, this work presents a systematic survey of this field and introduces an innovative multidimensional taxonomy framework based on target scale, sensor perception modes, and sensor collaboration patterns. Within this framework, we comprehensively survey the literature (more than 180 publications) over the period 2016-2025, spanning from the theoretical foundations to diverse algorithmic approaches in underwater acoustic target tracking. Particularly, we emphasize the transformative potential and recent advancements of machine learning techniques, including deep learning and reinforcement learning, in enhancing the performance and adaptability of underwater tracking systems. Finally, this survey concludes by identifying key challenges in the field and proposing future avenues based on emerging technologies such as federated learning, blockchain, embodied intelligence, and large models.

Jovan Komatovic, Andrew Lewis-Pye, Joachim Neu, Tim Roughgarden · 5 authors

This paper presents the first generic compiler that transforms any permissioned consensus protocol into a proof-of-stake permissionless consensus protocol. For each of the following properties, if the initial permissioned protocol satisfies that property in the partially synchronous setting, the consequent proof-of-stake protocol also satisfies that property in the partially synchronous and quasi-permissionless setting (with the same fault-tolerance): consistency; liveness; optimistic responsiveness; every composable log-specific property; and message complexity of a given order. Moreover, our transformation ensures that the output protocol satisfies accountability (identifying culprits in the event of a consistency violation), whether or not the original permissioned protocol satisfied it.

Rezki Akbar Norrahman

Sharia fintech is a digital financial innovation that integrates technology with sharia principles, one of which is through a Peer To Peer (P2P) lending platform. However, in practice, various sharia compliance issues are still found, such as the potential for usury, gharar, and non compliance with contracts. This is due to limited manual supervision and the complexity of digital transactions. This study aims to analyze the potential for implementing smart contract technology to improve sharia compliance on P2P lending platforms. Using a qualitative approach through literature studies, this article examines how smart contract characteristics such as transparency, automation, auditability, and resistance to manipulation can support the implementation of sharia contracts such as murabahah, mudharabah, and musyarakah. The results of the study show that smart contracts enable the automatic implementation of sharia compliant transactions, reject unauthorized processes, and provide an immutable blockchain based monitoring and reporting system. This potential makes it a strategic tool in building a more accountable, efficient, and trusted sharia fintech ecosystem. However, the implementation of this technology still faces challenges, such as limited regulations, the need for multidisciplinary human resources, and low digital sharia literacy. Therefore, collaboration between scholars, regulators, and technology developers is needed to ensure that the implementation of smart contracts is not only technically superior, but also in accordance with the maqashid sharia. This study recommends the development of prototypes and further empirical research as concrete steps for implementation.

Authors unavailable

Based on the document content, I'll create a comprehensive abstract that captures the key aspects of the research. The research investigates the performance and efficiency of various consumer banking platforms using Grey Relational Analysis (GRA). The study analyzed five distinct banking platforms—Online Banks (Nedbank's), Credit Unions, Peer-to-Peer (P2P) Lending, Fintech Solutions, and Cryptocurrency/Decentralized Finance (Deify)—across four critical dimensions: Customer Satisfaction, Digital Banking and Technology, Financial Products and Services, and Customer Support. The analysis employed normalized data, deviation sequences, and grey relation coefficients to establish comprehensive performance metrics. The findings reveal significant variations in platform effectiveness, with Fintech solutions achieving the highest Grey Relationship Grade (GRG: 0.7387), followed closely by P2P lending (GRG: 0.7064). Traditional platforms like Credit Unions maintained moderate performance (GRG: 0.5674), while Cryptocurrency/Deify (GRG: 0.5117) and Online Banks (GRG: 0.5115) showed considerable room for improvement. The research demonstrates that success in modern banking requires a balanced integration of technological innovation with customer-centric services, rather than excellence in isolated areas. These results hold significant importance for shaping the strategic growth of banking services and guiding the future advancement of financial technology platforms.

Jundullah Rifqi Prasmanto, Anang Ma’ruf, Muhammad Fathurrahman Assidiq, Muhammad Faiz Diyaulhaq

This study examines the status of Bitcoin and its underlying blockchain technology from the perspective of Islamic law. The research utilizes a qualitative library-based method, analyzing primary sources of Islamic jurisprudence alongside recent academic studies. It explores key Shariah principles such as mal mutaqawwam, maysir, gharar, and riba, in assessing Bitcoin's permissibility. The findings reveal that while Bitcoin's volatility, speculation, and lack of intrinsic value raise concerns under Islamic finance, the asset does not inherently involve interest (riba). Furthermore, the research distinguishes between the controversial nature of Bitcoin and the positive potential of blockchain technology, which aligns with the objectives of maqasid al-shariah, particularly in promoting transparency, financial inclusion, and ethical conduct. The study concludes that while Bitcoin may remain contentious, blockchain offers significant opportunities for Shariah-compliant financial innovation when supported by appropriate regulation and ethical oversight.

E. Samatha Sree Chaturved

Abstract Keeping medical data safe and private has become a big challenge with the fast-growing digital healthcare systems. Old security methods are not strong enough to stop hacking and unauthorized access. This paper introduces an Integrated Privacy Preservation and Blockchain (IPPB) model to make medical data sharing secure. The model uses blockchain to create a decentralized and unchangeable record that ensures data accuracy, precise tracking, and controlled access. It also applies strong encryption methods like homomorphic encryption and zero-knowledge proofs (ZKP) to protect patient information while allowing safe data sharing between healthcare providers. A lightweight approval method is used to make the system faster, which lowers the usual heavy processing of blockchain networks, making it better for real-time medical use. An intelligent contract- based access system ensures that only allowed users can see the data while keeping track of who accessed it. Tests show that the IPPB model works better than current security methods by improving speed, maintaining private data, and defending against cyber threats. The results prove that adding blockchain to privacy systems can make medical data more secure, trustworthy, and easy to share, making it useful for future healthcare systems. Keywords: Privacy Preservation, Blockchain, Medical Data Security, Homomorphic Encryption, Smart Contracts, Secure Data Transmission, Cybersecurity in Healthcare.

Xuechun Mao, Xiaqing Zhou, Xiaoming Zhao, Ying Chen

The widespread adoption of e-health systems raises critical concerns regarding data privacy and network security. Ensuring secure and reliable data sharing between patients and healthcare professionals remains a significant challenge. To address this, we propose a novel anonymous authentication scheme tailored for e-health environments, integrating zero-knowledge proof (ZKP) with multimodal biometrics. Our key contributions are as follows: (1) applying the Pedersen vector commitment algorithm to construct a biometric-based ZKP scheme, thereby ensuring enhanced security and privacy-preserving authentication; (2) utilizing multimodal cancelable biometrics generate (MCBG) technology, integrating fingerprint, face, and iris modalities to strengthen the security of the verification process; and (3) providing a detailed security analysis that demonstrates our scheme meets essential security requirements, including anonymity, authenticity, unlinkability, forward security, and resistance to replay attacks. Experimental results demonstrate stable proving and verification time of approximately 78 ms and 140 ms, respectively, regardless of the proof range, validating its efficiency and practicality for secure authentication in e-health systems.

Isaac Kofi Nti, Owusu Nyarko-Boateng, Samuel Boateng, Benjamin Asubam Weyori · 5 authors

No abstract is available for this record.