Blockchain-Research and Applications最新文献

{"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":"2025-06-01","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":"2025-06-01","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":"An efficient Bitcoin network topology discovery algorithm for dynamic display","authors":"Zening Zhao ,&nbsp;Jinsong Wang ,&nbsp;Miao Yang ,&nbsp;Haitao Wang","doi":"10.1016/j.bcra.2024.100260","DOIUrl":"10.1016/j.bcra.2024.100260","url":null,"abstract":"<div><div>The Bitcoin network comprises numerous nodes, necessitating users to invest significant network requests and time in comprehending its network topology. In this paper, we propose a Bitcoin network topology discovery algorithm that uses lightweight probe nodes to facilitate rapid transmission of network protocols. Building upon this, we introduce a node layer clustering algorithm based on filtering stable network nodes, enabling parallel discovery of the network topology. Additionally, we present an adaptive method for dynamically displaying the layered structure of the network topology. Experimental results demonstrate that our proposed method reduces communication overhead by approximately 72.16% when achieving a 95% similarity in network topology. Furthermore, the algorithm is applicable for discovering the network topology in other blockchain networks with similar structures.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100260"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307968","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":"2025-06-01","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":"A blockchain based efficient incentive mechanism in tripartite cyber threat intelligence service marketplace","authors":"Yuan Zhou ,&nbsp;Yaoyao Zhang ,&nbsp;Qinglin Yang ,&nbsp;Yuan Liu ,&nbsp;Chunming Rong ,&nbsp;Zhihong Tian","doi":"10.1016/j.bcra.2024.100263","DOIUrl":"10.1016/j.bcra.2024.100263","url":null,"abstract":"<div><div>The Cyber Threat Intelligence (CTI) marketplace is an emerging platform for CTI service requesters to countermeasure advanced cyber attacks, where CTI service providers are employed on payment. To create a trustworthy CTI marketplace environment, consortium-blockchain-based CTI service platforms have been widely proposed, where the blockchain system becomes the third role, crucially impacting the CTI service quality. How to sustainably promote CTI service quality in this tripartite marketplace is a challenging issue, which has not been well investigated in the literature. In this study, we propose a two-stage tripartite dynamic game-model-based incentive mechanism, where the participation incentives of the three parties are promoted under the constraints of Individual Rationality (IR) and Incentive Compatibility (IC). The sustainability of CTI service is quantitatively formalized through the CTI market demand, which impacts the future profits of the three parties. The Nash equilibrium of the proposed incentive mechanism is solved, where the CTI requester offers an optimal price to achieve effective defense against cyber attacks, and the blockchain platform and CTI service providers collaboratively contribute high-quality CTI services. Empirical experimental results show that the higher the quality of CTI services provided in the marketplace, the greater the market demand for CTI, resulting in a sustainable CTI marketplace.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100263"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307966","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":"SmartZKCP: Towards practical data exchange marketplace against active attacks","authors":"Xuanming Liu ,&nbsp;Jiawen Zhang ,&nbsp;Yinghao Wang ,&nbsp;Xinpeng Yang ,&nbsp;Xiaohu Yang","doi":"10.1016/j.bcra.2024.100272","DOIUrl":"10.1016/j.bcra.2024.100272","url":null,"abstract":"<div><div>The trading of data is becoming increasingly important as it holds substantial value. A blockchain-based data marketplace can provide a secure and transparent platform for data exchange. To facilitate this, developing a fair data exchange protocol for digital goods has garnered considerable attention in recent decades. The Zero Knowledge Contingent Payment (ZKCP) protocol enables trustless fair exchanges with the aid of blockchain and zero-knowledge proofs. However, applying this protocol in a practical data marketplace is not trivial.</div><div>In this paper, several potential attacks are identified when applying the ZKCP protocol in a practical public data marketplace. To address these issues, we propose SmartZKCP, an enhanced solution that offers improved security measures and increased performance. The protocol is formalized to ensure fairness and secure against potential attacks. Moreover, SmartZKCP offers efficiency optimizations and minimized communication costs. Evaluation results show that SmartZKCP is both practical and efficient, making it applicable in a data exchange marketplace.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100272"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144270707","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":"2025-06-01","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":"DeFi risk assessment: MakerDAO loan portfolio case","authors":"Ignat Melnikov ,&nbsp;Irina Lebedeva ,&nbsp;Artem Petrov ,&nbsp;Yury Yanovich","doi":"10.1016/j.bcra.2024.100259","DOIUrl":"10.1016/j.bcra.2024.100259","url":null,"abstract":"<div><div>Decentralized finance (DeFi) is a rapidly evolving blockchain technology that offers a new perspective on financial services through Web3 applications. DeFi offers developers the flexibility to create financial services using smart contracts, leading to a lack of standardized protocols and challenges in applying traditional finance models for risk assessment, especially in the early stages of adoption. The Maker protocol is a prominent DeFi platform known for its diverse functionalities, including loan services. This study focuses on analyzing the risk associated with Maker's loan portfolio by developing a risk model based on multiple Brownian motions and passage levels, with Brownian motions representing different collateral types and passage levels representing users' collateralization ratios. Through numerical experiments using artificial and real data, we evaluate the model's effectiveness in assessing risk within the loan portfolio. While our findings demonstrate the model's potential for assessing risk within a single DeFi project, it is important to acknowledge that the model's assumptions may not be fully applicable to real-world data. This research underscores the importance of developing project-specific risk assessment models for individual DeFi projects and encourages further exploration of other DeFi protocols.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100259"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190436","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":"Atomic and privacy-preserving cyclic cross-chain protocol based on chameleon hash function","authors":"Mengyan Li,&nbsp;Maoning Wang,&nbsp;Meijiao Duan","doi":"10.1016/j.bcra.2024.100262","DOIUrl":"10.1016/j.bcra.2024.100262","url":null,"abstract":"<div><div>Blockchain-based digital assets have increasingly emerged in recent years, necessitating cross-chain swaps. Hash Time-Lock Contract (HTLC) is a widely used protocol for such swaps; however, simple hash time locks can allow attackers to analyze transaction paths, thereby causing privacy breaches and financial loss to users in some sensitive scenarios. To prevent payment path leakage, a privacy-preserving cyclic cross-chain protocol is proposed herein. This protocol primarily uses the Chameleon Hash (CH) protocol to obscure the correlation between users in the path, ensuring the privacy of cross-chain swaps. The protocol is divided into pre-swap, commit, and decommit phases. The pre-swap phase is firstly executed to determine the swap order. Then, users ensure atomicity via serial asset locking in the commit phase, and each receiver obtains swap assets from the corresponding sender via CH collision in the decommit phase. The security proof under the Universally Composable (UC) system demonstrates the correctness and usability of the protocol. In summary, the entire protocol ensures the atomicity and privacy of cross-chain swaps, providing a new principle and method to solve the privacy leakage problem caused by transaction path analysis.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100262"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307954","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":"2025-06-01","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}