IET Blockchain最新文献

{"title":"Blockchain based intelligent disbursement in National Scholarship Portal","authors":"Lifna Challissery Samu,&nbsp;Neelkanth Khithani,&nbsp;Kushl Alve,&nbsp;Vedang Gambhire,&nbsp;Atharva Hande,&nbsp;Shivam Choubey","doi":"10.1049/blc2.12092","DOIUrl":"https://doi.org/10.1049/blc2.12092","url":null,"abstract":"<p>The National Scholarship Portal in India serves as a one-stop solution for students seeking financial aid for their studies across the country. However, in this digital era, the national-level portal faces challenges such as limited provision for only government scholarships, non-automated systems, complex application processes, reliance on physical verifications, and delays in scholarship disbursement. This research proposes a blockchain-based scholarship module to address these challenges and automate the entire scholarship process. The paper emphasizes upon the transformative impact by the usage of Hyperledger fabric network, which provides a fool-proof system that streamlines the entire application process and fund disbursement. The proposed integration also ensures robust application verification, accountability of stakeholders, transparent scholarship selection criteria, automated and thorough tracking of fund disbursement, immutable transaction history, secure authorization; and stringent compliance measures. Thus, the implementation of the proposed system aims to alleviate the financial insecurities faced by students during their studies, simplify their search for scholarship opportunities, and enable them to focus more on their academic pursuits.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 4","pages":"407-422"},"PeriodicalIF":0.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy preserving large language models: ChatGPT case study based vision and framework","authors":"Imdad Ullah,&nbsp;Najm Hassan,&nbsp;Sukhpal Singh Gill,&nbsp;Basem Suleiman,&nbsp;Tariq Ahamed Ahanger,&nbsp;Zawar Shah,&nbsp;Junaid Qadir,&nbsp;Salil S. Kanhere","doi":"10.1049/blc2.12091","DOIUrl":"https://doi.org/10.1049/blc2.12091","url":null,"abstract":"<p>The generative Artificial Intelligence (AI) tools based on Large Language Models (LLMs) use billions of parameters to extensively analyse large datasets and extract critical information such as context, specific details, identifying information, use this information in the training process, and generate responses for the requested queries. The extracted data also contain sensitive information, seriously threatening user privacy and reluctance to use such tools. This article proposes the conceptual model called PrivChatGPT, a privacy-preserving model for LLMs consisting of two main components, that is, preserving user privacy during the data curation/pre-processing and preserving private context and the private training process for large-scale data. To demonstrate the applicability of PrivChatGPT, it is shown how a private mechanism could be integrated into the existing model for training LLMs to protect user privacy; specifically, differential privacy and private training using Reinforcement Learning (RL) were employed. The privacy level probabilities are associated with the document contents, including the private contextual information, and with metadata, which is used to evaluate the disclosure probability loss for an individual's private information. The privacy loss is measured and the measure of uncertainty or randomness is evaluated using entropy once differential privacy is applied. It recursively evaluates the level of privacy guarantees and the uncertainty of public databases and resources during each update when new information is added for training purposes. To critically evaluate the use of differential privacy for private LLMs, other mechanisms were hypothetically compared such as Blockchain, private information retrieval, randomisation, obfuscation, anonymisation, and the use of Tor for various performance measures such as the model performance and accuracy, computational complexity, privacy vs. utility, training latency, vulnerability to attacks, and resource consumption. It is concluded that differential privacy, randomisation, and obfuscation can impact the training models' utility and performance; conversely, using Tor, Blockchain, and Private Information Retrieval (PIR) may introduce additional computational complexity and high training latency. It is believed that the proposed model could be used as a benchmark for privacy-preserving LLMs for generative AI tools.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"706-724"},"PeriodicalIF":0.0,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"zk-STARKs based scheme for sealed auctions in chains","authors":"Li Wei,&nbsp;Liang Peili,&nbsp;Li Fei","doi":"10.1049/blc2.12090","DOIUrl":"https://doi.org/10.1049/blc2.12090","url":null,"abstract":"<p>On-chain sealed auctions represent a novel approach to electronic bidding auctions, wherein the introduction of zero-knowledge proof technology has significantly enhanced the security of auctions. However, most mainstream on-chain sealed auction schemes currently employ Bulletproofs to prove auction correctness, which leaves room for optimization in terms of verification time and inherent security. Addressing these issues, an on-chain sealed auction scheme based on zero-knowledge succinct non-interactive argument of knowledge (zk-STARK) is proposed. This scheme leverages the decentralization and immutability of blockchain and smart contracts to eliminate third-party involvement while ensuring the security of the auction process. The Inter Planetary File System is utilized to provide a qualification review mechanism for the auctioneer, enabling the screening of unqualified bidders before the auction. Additionally, the scheme employs RSA encryption to conceal bidders' bids, Pedersen commitments to ensure the consistency of bidding information, and zk-STARKs to verify the correctness of the winning bid. Security analysis and experimental results demonstrate that the proposed scheme meets the required security standards, with time consumption at various stages of the auction being within acceptable limits, and effectively reduces the time required for proof verification.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 4","pages":"344-354"},"PeriodicalIF":0.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling smurfing patterns in cryptocurrencies with integer partitions","authors":"Marlene Koelbing,&nbsp;Klaus Kieseberg,&nbsp;Ceren Çulha,&nbsp;Bernhard Garn,&nbsp;Dimitris E. Simos","doi":"10.1049/blc2.12087","DOIUrl":"https://doi.org/10.1049/blc2.12087","url":null,"abstract":"<p>In this paper, we propose the modelling of patterns of financial transactions - with a focus on the domain of cryptocurrencies - as splittings and present a method for generating such splittings utilizing integer partitions. We study current money laundering regulations and directives concerning thresholds for monitoring of financial transactions. We further exemplify that, by having the partitions respect these threshold criteria, the splittings generated from them can be used for modelling illicit transactional behavior such as is shown by smurfing. In addition, we conduct an analysis of the splittings occurring in money laundering efforts that took place in the aftermath of the Upbit hack. Based on the potential weaknesses identified by our research, we finally provide suggestions on how to improve current AML techniques and initiatives towards more effective AML efforts.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"659-680"},"PeriodicalIF":0.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective energy management system for multi-microgrids using blockchain miners: A two-stage peak shaving and valley filling framework","authors":"Payman Rezaei,&nbsp;Masoud AliAkbar Golkar","doi":"10.1049/blc2.12088","DOIUrl":"https://doi.org/10.1049/blc2.12088","url":null,"abstract":"<p>This study presents an innovative energy management framework for multi-microgrids, integrating the burgeoning domain of cryptocurrency mining. Cryptocurrencies, a novel fusion of encryption technology and financial currency, are witnessing exponential global growth. This expansion correlates with a surge in the prevalence of mining activities, amplifying electricity consumption and necessitating accelerated advancements in urban transmission and distribution infrastructures, coupled with increased financial investments. Despite cryptocurrencies' growth, comprehensive research to capitalize on their potential is scarce. This article introduces an operation cost model for miners in the proposed dual-stage framework. The first stage is dedicated to day-ahead scheduling, focusing on peak shaving and valley filling in the electricity demand curve, while concurrently optimizing operational costs. The second stage, updating each 5 min, minimizes imbalances in response to uncertain network conditions. A pivotal feature of this framework is the allocation of revenues generated from mining operations towards enhancing renewable energy resources. Empirical simulations underscore the framework's efficacy, evidenced by a substantial peak shaving of 482.833 kW and valley filling of 4084.42 kW. Furthermore, this approach effectively maintains operational costs within a feasible spectrum. Notably, the demand curve's peak-to-valley distance extends to 4 MW, with the revenue from mining activities alone sufficient to offset operational expenditures.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"616-631"},"PeriodicalIF":0.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secure data sharing technology of medical privacy data in the Web 3.0","authors":"Shusheng Guo,&nbsp;Cheng Chen,&nbsp;Qing Tong","doi":"10.1049/blc2.12086","DOIUrl":"https://doi.org/10.1049/blc2.12086","url":null,"abstract":"<p>The development of Web 3.0 technology may signify the dawn of a new digital era. Its concepts of co-management, co-construction, and sharing address the need for private data sharing among medical institutions. However, the sharing of private data has been challenging due to the lack of effective monitoring methods and authorization mechanisms. Additionally, controlling the scope of data sharing, providing incentives, and ensuring legal compliance have presented difficulties. To this end, a medical privacy data security sharing model based on key technologies of Web 3.0 has been proposed and implemented. It stores the source data in Inter Planetary File System by constructing an index of private data keywords, generates trapdoors using query keywords, and achieves retrieval of ciphertext data. Finally, data users apply to multiple parties for joint secure computing to obtain the use of private data. The experimental results indicate that when the size of the private data is less than 5 MB, with 3000 ciphertext indexes and three search keywords, both encryption and decryption times are around 50 ms, and the retrieval time is approximately 1.6 s. This performance is adequate for typical medical privacy sharing and computing scenarios.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 4","pages":"335-343"},"PeriodicalIF":0.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serein: A parallel pipeline-based DAG schema for consensus in blockchain","authors":"Yang Liu,&nbsp;Jingwen Chen,&nbsp;Miaomiao Zhang,&nbsp;Shidong Shi,&nbsp;Feng Wang","doi":"10.1049/blc2.12085","DOIUrl":"https://doi.org/10.1049/blc2.12085","url":null,"abstract":"<p>As the core technology of blockchain, consensus mechanisms play a crucial role in ensuring the consistency and reliability of blockchain systems. In a decentralized and open system environment like blockchain, traditional consensus algorithms are often unsuitable due to their inability to tolerate arbitrary faults such as malicious node behaviour. Consequently, Byzantine fault tolerance consensus algorithms have become a focal point in blockchain systems. However, as Byzantine fault tolerance consensus algorithms have evolved, they still face significant challenges, particularly in addressing issues related to network latency and throughput. This paper proposes a parallel pipeline-based DAG schema for consensus in blockchain, Serein. Firstly, the Serein algorithm achieves functional partitioning of nodes, enhancing their scalability. Secondly, it employs a pipeline structure, allowing each block to proceed without waiting for the previous block's result, thereby reducing block generation latency. Lastly, the Serein algorithm leverages the advantages of the DAG block structure to achieve concurrent block ordering and submission, improving system throughput. Experimental results demonstrate that the proposed Serein algorithm maintains robust performance under conditions of high transaction volume with multiple nodes, effectively enhancing consensus efficiency while ensuring Byzantine fault-tolerant security.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"681-690"},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable data management in global health crises: Leveraging blockchain technology","authors":"Sakib Al Jobaid,&nbsp;Upama Kabir,&nbsp;Mosarrat Jahan","doi":"10.1049/blc2.12084","DOIUrl":"https://doi.org/10.1049/blc2.12084","url":null,"abstract":"<p>Effective data management is crucial in navigating any health crisis. With proper data management protocols in place, stakeholders can swiftly adapt to evolving circumstances during challenging times. A recent event like the COVID-19 pandemic has unequivocally revealed its significance. It is essential to conduct disease surveillance, practice preventive measures, and devise policies to contain the situation. As the process involves massive data growth, it demands an acute level of oversight and control. Monitoring this vast sensitive data faces multifaceted limitations, namely data tampering, breach of privacy, and centralized data stewardship. In response to these challenges, we propose an innovative blockchain-enabled scalable data management scheme in light of the COVID-19 scenario. However, blockchain cannot scale in a large ecosystem due to storing all contents in every participating node. This work addresses this shortcoming by proposing a lightweight solution that groups nodes into clusters, resulting in less memory and processing overhead. Moreover, it adopts an off-chaining technique to reduce the memory load of every node and, thereby, the entire network. The experimental results demonstrate that it attains approximately 85% and 94% storage reduction per node and the whole network, respectively, and an 87% reduction in transaction processing time.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"596-615"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143244221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain transaction data mining and its applications","authors":"Jiajing Wu,&nbsp;Hong-Ning Dai,&nbsp;Qi Xuan,&nbsp;Radosław Michalski,&nbsp;Xi Chen","doi":"10.1049/blc2.12083","DOIUrl":"https://doi.org/10.1049/blc2.12083","url":null,"abstract":"&lt;p&gt;Since the birth of blockchain as the underlying support technology for Bitcoin, blockchain technology has received widespread attention from academia and industry worldwide and is considered to have profound potential for disruptive change in areas such as finance, smart manufacturing, and the Internet of Things. As cryptocurrencies, smart contracts, decentralized applications and other derivatives continue to be generated on the blockchain, the volume of transaction data on the blockchain has been maintaining a high growth. With the help of this massive data, we can dig out the development rules of the blockchain, analyze the characteristics of different transactions, and then identify the abnormal behaviour on the blockchain to promote the green and sustainable development of the blockchain. Unfortunately, blockchain transaction data mining faces challenges, such as blockchain data heterogeneity, anonymity and decentralization as well as real-time and generality.&lt;/p&gt;&lt;p&gt;This special issue aims to provide an open venue for academic and industrial communities to present and discuss cutting-edge technologies and research results regarding blockchain transaction data mining and its applications. It solicits original high-quality papers with new transaction data acquisition tools, transaction network construction and mining methods, anomaly detection algorithms, etc.&lt;/p&gt;&lt;p&gt;In this Special Issue, we have received eight papers, all of which underwent peer review. Of the eight originally submitted papers, five have been accepted. The overall submissions were of high quality, which marks the success of this Special Issue. A brief presentation of each of the paper in this special issue follows.&lt;/p&gt;&lt;p&gt;Xiong et al. introduce a graph neural network-based phishing detection method for Ethereum, and conduct extensive experiments on the Ethereum dataset to verify the effectiveness of this scheme in identifying Ethereum phishing detection. The method introduces a feature learning algorithm named TransWalk and constructs an Ethereum phishing fraud detection framework utilizing a transaction-oriented biased sampling strategy for transaction networks and a multi-scale feature extraction method for Ethereum. Through more effective extraction of Ethereum transaction features, the framework aims to enhance phishing fraud detection performance. This work holds significant importance in the field of Ethereum ecosystem security. Access the full paper using the following link: https://doi.org/10.1049/blc2.12031.&lt;/p&gt;&lt;p&gt;Feng et al. propose a framework for detecting and repairing reentrancy vulnerabilities in smart contracts based on bytecode and vulnerability features. This framework aims to mitigate the losses incurred by reentrancy vulnerabilities in the digital currency economy and offers a more comprehensive solution for detecting and repairing such vulnerabilities. The proposed bytecode-level method overcomes challenges in detection and repair by integrating detecti","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 3","pages":"223-225"},"PeriodicalIF":0.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on transaction privacy protection solutions for cross-border commerce","authors":"JinCheng Ma,&nbsp;Fei Li","doi":"10.1049/blc2.12080","DOIUrl":"10.1049/blc2.12080","url":null,"abstract":"<p>In response to the dual privacy protection challenges concerning the confidentiality of transaction amounts and identities in cross-border trade, a transaction scheme that combines ⁺HomEIG Zero Knowledge Proof (⁺HomEIG-ZKProof) and the national encryption algorithm SM2 is proposed. While ensuring transaction traceability and verifiability, this scheme achieves privacy protection for both payers’ and recipients’ identities, specifically tailored for cross-border trade scenarios. Additionally, customs authorities play the role of supervisory nodes to verify the identities of transaction parties and the zero-knowledge proofs for transaction information. The RAFT consensus algorithm is employed to construct a secure authentication application, demonstrating how zero-knowledge proofs, combined with homomorphic encryption, can be verified through a consensus process. In this scenario, the legitimacy of transaction amounts is subject to zero-knowledge verification during consensus interactions. Merchant identity verification is accomplished using SM2 ring signatures. The analysis indicates that this scheme offers strong security features such as resistance to tampering attacks, public key replacement attacks, impersonation attacks, and anonymity. Testing results demonstrate that this scheme can effectively provide dual privacy protection for transaction amounts and identities in cross-border trade, meeting the practical requirements of privacy protection in cross-border trade transactions.</p>","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":"4 S1","pages":"586-595"},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/blc2.12080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}