Blockchain-Research and Applications最新文献

{"title":"βFSCM: An enhanced food supply chain management system using hybrid blockchain and recommender systems","authors":"Feiyang Sun ,&nbsp;Peiyu Wang ,&nbsp;Yihan Zhang ,&nbsp;Pushpendu Kar","doi":"10.1016/j.bcra.2024.100245","DOIUrl":"10.1016/j.bcra.2024.100245","url":null,"abstract":"<div><div>Blockchain technology has gained traction in Food Supply Chain Management (FSCM), enhancing traceability and transparency. The existing deployments of public or private blockchains face issues in achieving an optimal balance between transparency and decentralization. This work proposes a hybrid blockchain model complemented by an Access Control (AC) mechanism to bolster security, reliability, and usability within FSCM systems. Furthermore, the integration of a recommender system is proposed to utilize data analytics and machine learning for personalizing product offerings and optimizing inventory management, aiming to boost efficiency and consumer satisfaction. The synergy between the hybrid blockchain framework and the recommender system is anticipated to cultivate a more engaged, efficient, and gratified supply chain ecosystem. The model significantly enhances monitoring in 30% of the use cases and supports transparency in a quarter. It also reduces vulnerability cases by 20%. Inventory management is markedly improved, reducing overstock by 25%, confirming the effectiveness of the proposed hybrid blockchain approach.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100245"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"D-VRE: From a Jupyter-enabled private research environment to decentralized collaborative research ecosystem","authors":"Yuandou Wang ,&nbsp;Sheejan Tripathi ,&nbsp;Siamak Farshidi ,&nbsp;Zhiming Zhao","doi":"10.1016/j.bcra.2024.100244","DOIUrl":"10.1016/j.bcra.2024.100244","url":null,"abstract":"<div><div>Today, scientific research is increasingly becoming data-centric and compute-intensive, relying on data and models across distributed sources. However, challenges still exist in the traditional cooperation mode, given the high storage and computing costs, geolocation barriers, and local confidentiality regulations. The Jupyter environment has recently emerged and evolved into a vital virtual research environment for scientific computing, which researchers can use to scale computational analyses up to larger datasets and high-performance computing resources. Nevertheless, existing approaches lack robust support of a decentralized cooperation mode to unlock the full potential of decentralized collaborative scientific research, e.g., seamlessly secure data sharing. In this work, we change the basic structure and legacy norms of current research environments via the seamless integration of Jupyter with Ethereum blockchain capabilities. As such, it creates a Decentralized Virtual Research Environment (D-VRE) from private computational notebooks to a decentralized collaborative research ecosystem. We propose a novel architecture for the D-VRE and prototype some essential D-VRE elements for enabling secure data sharing with decentralized identity, user-centric agreement-making, membership, and research asset management. To validate our method, we conduct an experimental study to test all functionalities of D-VRE smart contracts and their gas consumption. In addition, we deploy the D-VRE prototype on a test net of the Ethereum blockchain for demonstration. The feedback from the studies showcases the current prototype's usability, ease of use, and potential, and suggests further improvements.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100244"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Backtesting framework for concentrated liquidity market makers on Uniswap V3 decentralized exchange","authors":"Andrey Urusov ,&nbsp;Rostislav Berezovskiy ,&nbsp;Yury Yanovich","doi":"10.1016/j.bcra.2024.100256","DOIUrl":"10.1016/j.bcra.2024.100256","url":null,"abstract":"<div><div>Decentralized Finance (DeFi) has revolutionized the financial landscape, with protocols like Uniswap offering innovative automated market-making mechanisms. This article explores the development of a backtesting framework specifically tailored for Concentrated Liquidity Market Makers (CLMMs). The focus is on leveraging the liquidity distribution approximated using a parametric model to estimate the rewards within liquidity pools. The article details the design, implementation, and insights derived from this novel approach to backtesting within the context of Uniswap V3. The developed backtester was successfully utilized to assess reward levels across several pools using historical data from 2023 (pools Uniswap V3 for pairs of altcoins, stablecoins, and USDC/ETH with different fee levels). Moreover, the error in modeling the level of rewards for the period under review for each pool was less than 1%. This demonstrated the effectiveness of the backtester in quantifying liquidity pool rewards and its potential in estimating revenues of Liquidity Provider (LP) as part of the pool rewards, which is the focus of our next research. The backtester serves as a tool to simulate trading strategies and liquidity provision scenarios, providing a quantitative assessment of potential returns for LPs. By incorporating statistical tools to mirror CLMM pool liquidity dynamics, this framework can be further leveraged for strategy enhancement and risk evaluation for LPs operating within decentralized exchanges.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100256"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SSI-MedRx: A fraud-resilient healthcare system based on blockchain and SSI","authors":"Meriem Guerar ,&nbsp;Mauro Migliardi ,&nbsp;Enrico Russo ,&nbsp;Djamel Khadraoui ,&nbsp;Alessio Merlo","doi":"10.1016/j.bcra.2024.100242","DOIUrl":"10.1016/j.bcra.2024.100242","url":null,"abstract":"<div><div>Today, healthcare fraud poses a significant issue, encompassing everything from falsified billing claims and phantom services to the excessive prescription of opioid medications and medical identity theft. These deceptive activities cause substantial financial losses, erode patient trust, compromise healthcare quality, and threaten patient safety. In this paper, we introduce SSI-MedRx, a healthcare system based on blockchain technology and Self-Sovereign Identity (SSI). It is designed to ensure cross-border interoperability, preserve patient privacy, and prevent challenging healthcare frauds, including medical identity theft, phantom billing, kickbacks, and opioid overprescribing. By design, our system empowers patients by granting them complete control over their personal and health data. This shift toward patient-centric data management can potentially reduce the risk of data breaches, enhance care coordination, and improve overall healthcare outcomes.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100242"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-driven innovation in fashion supply chain contractual party evaluations as an emerging collaboration model","authors":"Minhao Qiao ,&nbsp;Xuanchang Chen ,&nbsp;Yangping Zhou ,&nbsp;P.Y. Mok","doi":"10.1016/j.bcra.2024.100266","DOIUrl":"10.1016/j.bcra.2024.100266","url":null,"abstract":"<div><div>With the advancement of distributed digital technology, the fashion supply chain management system is undergoing unprecedented transformations. Given the expansion and rapid iteration of the fashion industry, traditional supply chain management models struggle to adapt to the volatile market changes. In this context, small and medium-sized enterprises (SMEs), which are integral components of the fashion supply chain, often face significant market pressure, leading to losses and even bankruptcy, which in turn causes delays across the entire supply chain. Thus, there is an urgent need for these businesses to adopt new technologies to reduce risks and achieve profitability. Although there have been attempts to introduce blockchain technology into the fashion supply chain, most of these efforts are still in the preliminary stages, with operations continuing to follow old methods. Therefore, this study aims to introduce an evaluation mechanism into the fashion supply chain, encouraging a collective maintenance of interests among SMEs. The main contribution of this paper includes the introduction of a set of innovative management evaluation mechanisms and collaboration models for SMEs in the fashion supply chain, with the goal of securing their rights to autonomous pricing and promoting healthy competition in the forthcoming Web 3.0 era. We implemented the enterprise-level consortium blockchain framework, Hyperledger Fabric. Through testing, it has been proven that the platform is effective and usable in ensuring data integrity and source transparency.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100266"},"PeriodicalIF":6.9,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering autonomous IoT devices in blockchain through gasless transactions","authors":"Yash Madhwal ,&nbsp;Yury Yanovich ,&nbsp;Aleksandra Korotkevich ,&nbsp;Daria Parshina ,&nbsp;Nshteh Seropian ,&nbsp;Stepan Gavrilov ,&nbsp;Alex Nikolaev ,&nbsp;S. Balachander ,&nbsp;A. Murugan","doi":"10.1016/j.bcra.2024.100257","DOIUrl":"10.1016/j.bcra.2024.100257","url":null,"abstract":"<div><div>The article introduces a proof-of-concept (PoC) that demonstrates the management of Internet of Things (IoT) devices' infrastructure via smart contracts, facilitating their interaction with the blockchain through gasless transactions. The focus is empowering IoT devices to autonomously sign transactions using their verified private keys, eliminating the necessity for external wallets and enabling blockchain interaction using Biconomy without incurring gas fees. In this PoC, managers can validate IoT devices, permitting them to transmit transactions securely without being able to manipulate measurements or risking losing crypto assets in case of hardware malfunctions. This innovative method ensures that devices with minimal funds can access sensor data and communicate with a smart contract on the blockchain to update information utilizing account abstraction. Detailed workflow and simulation results are provided to showcase the practicality and advantages of this approach in scenarios demanding seamless automated blockchain engagement through IoT devices. The PoC code is openly accessible on GitHub, enhancing the transparency and accessibility of our research outcomes.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100257"},"PeriodicalIF":6.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"πFL: Private, atomic, incentive mechanism for federated learning based on blockchain","authors":"Kejia Chen ,&nbsp;Jiawen Zhang ,&nbsp;Xuanming Liu ,&nbsp;Zunlei Feng ,&nbsp;Xiaohu Yang","doi":"10.1016/j.bcra.2024.100271","DOIUrl":"10.1016/j.bcra.2024.100271","url":null,"abstract":"<div><div>Federated learning (FL) is predicated on the provision of high-quality data by multiple clients, which is then used to train global models. A plethora of incentive mechanism studies have been conducted with the objective of promoting the provision of high-quality data by clients. These studies have focused on the distribution of benefits to clients. However, the incentives of federated learning are transactional in nature, and the issue of the atomicity of transactions has not been addressed. Furthermore, the data quality of individual clients participating in training varies, and they may participate negatively in training out of privacy leakage concerns.</div><div>Consequently, we propose an inaugural atomistic incentive scheme with privacy preservation in the FL setting: <em>π</em>FL (<strong>p</strong>rivacy, <strong>a</strong>tomic, <strong>i</strong>ncentive). This scheme establishes a more dependable training environment based on Shapley valuation, secure multi-party computation, and smart contracts. Consequently, it ensures that each client's contribution can be accurately measured and appropriately rewarded, improves the accuracy and efficiency of model training, and enhances the sustainability and reliability of the FL system. The efficacy of this mechanism has been demonstrated through comprehensive experimental analysis. It is evident that this mechanism not only protects the privacy of trainers and provides atomic training rewards but also improves the model performance of FL, with an accuracy improvement of at least 8%.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100271"},"PeriodicalIF":6.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144146941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"To healthier Ethereum: a comprehensive and iterative smart contract weakness enumeration","authors":"Jiachi Chen,&nbsp;Mingyuan Huang,&nbsp;Zewei Lin,&nbsp;Peilin Zheng,&nbsp;Zibin Zheng","doi":"10.1016/j.bcra.2024.100258","DOIUrl":"10.1016/j.bcra.2024.100258","url":null,"abstract":"<div><div>With the increasing popularity of cryptocurrencies and blockchain technologies, smart contracts have become a prominent feature in developing decentralized applications. However, these smart contracts are susceptible to vulnerabilities that hackers can exploit, resulting in significant financial losses. In response to this growing concern, various initiatives have emerged. Notably, the Smart Contract Weakness Classification (SWC) list plays an important role in raising awareness and understanding of smart contract weaknesses. However, the SWC list lacks maintenance and has not been updated with new vulnerabilities since 2020. To address this gap, this paper introduces the Smart Contract Weakness Enumeration (SWE), a comprehensive and practical vulnerability list up until 2023. We collect 273 vulnerability descriptions from 86 top conference papers and journal papers, employing the open card-sorting method to deduplicate and categorize these descriptions. This process results in the identification of 40 common contract weaknesses, which are further classified into 20 sub-research fields through thorough discussion and analysis. The SWE provides a systematic and comprehensive list of smart contract vulnerabilities, covering existing and emerging vulnerabilities in the last few years. Moreover, the SWE is a scalable and continuously iterative program. We propose two update mechanisms for the maintenance of the SWE. Regular updates involve the inclusion of new vulnerabilities from future top papers, while irregular updates enable individuals to report new weaknesses for review and potential addition to the SWE.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100258"},"PeriodicalIF":6.9,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset","authors":"Sepideh HajiHosseinKhani ,&nbsp;Arash Habibi Lashkari ,&nbsp;Ali Mizani Oskui","doi":"10.1016/j.bcra.2024.100253","DOIUrl":"10.1016/j.bcra.2024.100253","url":null,"abstract":"<div><div>With the advent of blockchain networks, there has been a transition from traditional contracts to Smart Contracts (SCs), which are crucial for maintaining trust within these networks. Previous methods for analyzing SCs vulnerabilities typically suffer from a lack of accuracy and effectiveness. Many of them, such as rule-based methods, machine learning techniques, and neural networks, also struggle to detect complex vulnerabilities due to limited data availability. This study introduces a novel approach to detecting, identifying, and profiling SC vulnerabilities, comprising two key components: an updated analyzer named SCsVulLyzer (V2.0) and an advanced Genetic Algorithm (GA) profiling method. The analyzer extracts 240 features across different categories, while the enhanced GA, explicitly designed for profiling SC vulnerabilities, employs techniques such as penalty fitness function, retention of elites, and adaptive mutation rate to create a detailed profile for each vulnerability. Furthermore, due to the lack of comprehensive validation and evaluation datasets with sufficient samples and diverse vulnerabilities, this work introduces a new dataset named BCCC-SCsVul-2024. This dataset consists of 111,897 Solidity source code samples, ensuring the practical validation of the proposed approach. Additionally, three types of taxonomies are established, covering SC literature review, profiling techniques, and feature extraction. These taxonomies offer a systematic classification and analysis of information, enhancing the efficiency of the proposed profiling technique. Our proposed approach demonstrated superior capabilities with higher precision and accuracy through rigorous testing and experimentation. It not only showed excellent results for evaluation parameters but also proved highly efficient in terms of time and space complexity. Moreover, the concept of the profiling technique makes our model highly transparent and explainable. These promising results highlight the potential of GA-based profiling to improve the detection and identification of SC vulnerabilities, contributing to enhanced security in blockchain networks.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100253"},"PeriodicalIF":6.9,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordinating REST interactions in service choreographies using blockchain","authors":"Francesco Donini ,&nbsp;Alessandro Marcelletti ,&nbsp;Andrea Morichetta ,&nbsp;Andrea Polini","doi":"10.1016/j.bcra.2024.100241","DOIUrl":"10.1016/j.bcra.2024.100241","url":null,"abstract":"<div><div>In Service Oriented Computing (SOC), different services interact and exchange information to reach specific objectives. To model interorganizational SOC systems, choreography modeling languages have emerged to represent the distributed coordination among the involved organizations. From the realization perspective, blockchain technology is emerging as a promising run-time supporting peer-to-peer communication technology without the need for a central coordinator, thanks to its intrinsic security, trust, and decentralization characteristics. However, while blockchain can bring many advantages, technological barriers still limit its adoption in organizations, due to the costly and time-consuming learning process. For this reason, we propose RESTChain, a framework that automatically enables the interactions that take place among the participants in a service choreography exploiting blockchain technology. Starting from a choreography specification, the framework provides a set of mediators and automatically generates a smart contract that coordinates the service interactions. The mediators are software components that are directly connected with the smart contracts and expose REpresentational State Transfer (REST) APIs in compliance with the role played by the organizations in the choreography. In this way, the services deployed by one organization can communicate with the services made available by another organization through the blockchain in a secure and transparent manner. The proposed approach has been implemented on the Layer 2 Polygon blockchain and validated in a market retail case study analyzing its efficiency in terms of time and cost.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100241"},"PeriodicalIF":6.9,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143100649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}