Blockchain-Research and Applications最新文献

{"title":"Implementation of blockchain technology in integrated IoT networks for constructing scalable ITS systems in India","authors":"Arya Kharche,&nbsp;Sanskar Badholia,&nbsp;Ram Krishna Upadhyay","doi":"10.1016/j.bcra.2024.100188","DOIUrl":"10.1016/j.bcra.2024.100188","url":null,"abstract":"<div><p>The implementation of blockchain technology in integrated IoT networks for constructing scalable Intelligent Transportation Systems (ITSs) in India has the potential to revolutionize the way we approach transportation. By leveraging the power of IoT and blockchain, we can create a highly secure, transparent, and efficient system that can transform the way we move people and goods. India, one of the world’s most populous countries, has a highly congested and inefficient transportation system that often leads to delays, accidents, and waste of time and resources. The integration of IoT and blockchain can help address these issues by enabling real-time monitoring, tracking, and optimization of traffic flows, thereby reducing congestion, improving safety, and increasing the overall efficiency of the transportation system. This paper explores the potential of blockchain technology in the context of integrated IoT networks for constructing scalable ITS systems in India. The methodology followed is to develop a proof-of-concept blockchain-based application for ITS, implement the blockchain solution into the existing ITS infrastructure, and ensure proper integration and compatibility with other systems. Conduct thorough research and maintenance to ensure the reliability and sustainability of such blockchain-based systems. This research discusses the various benefits and challenges of this approach and the various applications of this technology in the transportation sector, including the green sustainability concept. The results find various ways in which such implementations of blockchain and IoT-Machine Learning (IoT-ML) can revolutionize transportation systems.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100188"},"PeriodicalIF":6.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000010/pdfft?md5=f0df3bf2f2a306097761b6d525acf13d&pid=1-s2.0-S2096720924000010-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139393019","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":"Time-varying nexus and causality in the quantile between Google investor sentiment and cryptocurrency returns","authors":"Fatma Ben Hamadou,&nbsp;Taicir Mezghani,&nbsp;Mouna Boujelbène Abbes","doi":"10.1016/j.bcra.2023.100177","DOIUrl":"10.1016/j.bcra.2023.100177","url":null,"abstract":"<div><p>Understanding the interplay between investor sentiment and cryptocurrency returns has become a critical area of research. Indeed, this study aims to uncover the role of Google investor sentiment on cryptocurrency returns (including Bitcoin, Litecoin, Ethereum, and Tether), especially during the 2017–18 bubble (January 01, 2017, to December 31, 2018) and the COVID-19 pandemic (January 01, 2020, to March 15, 2022). To achieve this, we use two techniques: quantile causality and wavelet coherence. First, the quantile causality test revealed that investors’ optimistic sentiments have notably higher cryptocurrency returns, whereas pessimistic sentiments have significantly opposite effects. Moreover, the wavelet coherence analysis shows that co-movement between investor sentiment and Tether cannot be considered significant. This result supports the role of Tether as a stablecoin in portfolio diversification strategies. In fact, the findings will help investors improve the accuracy of cryptocurrency return forecasts in times of stressful events and pave the way for enhanced decision-making utility.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100177"},"PeriodicalIF":5.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000520/pdfft?md5=98182819a759cd071a476d4ffe8e903a&pid=1-s2.0-S2096720923000520-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139196126","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-based engine data trustworthy swarm learning management method","authors":"Zhenjie Luo,&nbsp;Hui Zhang","doi":"10.1016/j.bcra.2023.100185","DOIUrl":"10.1016/j.bcra.2023.100185","url":null,"abstract":"<div><p>Engine data management is of great significance for ensuring data security and sharing, as well as facilitating multi-party collaborative learning. Traditional data management approaches often involve decentralized data storage that is vulnerable to tampering, making it challenging to conduct multi-party collaborative learning under privacy protection conditions and fully leverage the value of data. Moreover, data with compromised integrity can lead to incorrect results if used for model training. Therefore, this paper aims to break down data sharing barriers and fully utilize decentralized data for multi-party collaborative learning under privacy protection conditions. We propose a trustworthy engine data management method based on blockchain technology to ensure data immutability and non-repudiation. To address the issue of limited data samples for some users resulting in poor model performance, we introduce swarm learning techniques based on centralized machine learning and design a trustworthy data management method for swarm learning, achieving trustworthy regulation of the entire process. We conduct research on engine models under swarm learning based on the NASA open dataset, effectively organizing decentralized data samples for collaborative training while ensuring data privacy and fully leveraging the value of data.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100185"},"PeriodicalIF":6.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S209672092300060X/pdfft?md5=3cecec9b4347c0153afcf9159a3b9bdc&pid=1-s2.0-S209672092300060X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139129817","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":"A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, challenges and solutions","authors":"Olusogo Popoola ,&nbsp;Marcos Rodrigues ,&nbsp;Jims Marchang ,&nbsp;Alex Shenfield ,&nbsp;Augustine Ikpehai ,&nbsp;Jumoke Popoola","doi":"10.1016/j.bcra.2023.100178","DOIUrl":"10.1016/j.bcra.2023.100178","url":null,"abstract":"<div><p>Protecting private data in smart homes, a popular Internet-of-Things (IoT) application, remains a significant data security and privacy challenge due to the large-scale development and distributed nature of IoT networks. Recently, smart healthcare has leveraged smart home systems, thereby compounding security concerns in terms of the confidentiality of sensitive and private data and by extension the privacy of the data owner. However, proof-of-authority (PoA)-based blockchain distributed ledger technology (DLT) has emerged as a promising solution for protecting private data from indiscriminate use and thereby preserving the privacy of individuals residing in IoT-enabled smart homes. This review elicits some concerns, issues, and problems that have hindered the adoption of blockchain and IoT (BCoT) in some domains and suggests requisite solutions using the aging-in-place scenario. Implementation issues with BCoT were examined as well as the combined challenges BCoT can pose when utilised for security gains. The study discusses recent findings, opportunities, and barriers, and provides recommendations that could facilitate the continuous growth of blockchain applications in healthcare. Lastly, the study explored the potential of using a PoA-based permission blockchain with an applicable consent-based privacy model for decision-making in the information disclosure process, including the use of publisher-subscriber contracts for fine-grained access control to ensure secure data processing and sharing, as well as ethical trust in personal information disclosure, as a solution direction. The proposed authorisation framework could guarantee data ownership, conditional access management, scalable and tamper-proof data storage, and a more resilient system against threat models such as interception and insider attacks.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100178"},"PeriodicalIF":6.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000532/pdfft?md5=430c94e12710b1fc82ce9b0e78f3eb2a&pid=1-s2.0-S2096720923000532-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139191753","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-based secure dining: Enhancing safety, transparency, and traceability in food consumption environment","authors":"Sachin Yele,&nbsp;Ratnesh Litoriya","doi":"10.1016/j.bcra.2023.100187","DOIUrl":"10.1016/j.bcra.2023.100187","url":null,"abstract":"<div><p>This research paper seeks to examine the possibilities of blockchain technology. For use in the field of restaurant food tracking and safety. Public health risks and economic costs are at stake when foodborne illness outbreaks occur, making food safety a top priority in the food industry. It can be difficult to quickly identify and address possible concerns about using traditional food traceability systems due to inefficiencies, data discrepancies, and a lack of transparency. In this study, we introduce a novel blockchain-based system developed especially for the purpose of tracking restaurant food. Blockchain decentralised consensus, immutability, and smart contracts are put to use in this system to provide trustworthy and transparent traceable infrastructure. Real-time monitoring and data collection along the food supply chain become possible when the blockchain architecture is combined with the Internet of Things (IoT) devices and RFID technology. We show that our proposed blockchain-based traceability solution is practical and efficient through a thorough assessment and validation procedure. The outcomes show that the system not only improves data quality and reliability but also drastically decreases the time and resources needed for food traceability. In addition, patrons are more likely to return to eateries that place a premium on food safety when they are given more information about the establishment’s practises. Additionally, we discuss scalability, data privacy, and interoperability concerns that may arise in future implementations and provide some initial ideas for overcoming these issues.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100187"},"PeriodicalIF":6.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000623/pdfft?md5=b81f2fd6ad7c0182a78d05469e8ac252&pid=1-s2.0-S2096720923000623-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139127783","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":"Trust in ESG reporting: The intelligent Veri-Green solution for incentivized verification","authors":"Liyuan Liu ,&nbsp;Zhiguo Ma ,&nbsp;Yiyun Zhou ,&nbsp;Melissa Fan ,&nbsp;Meng Han","doi":"10.1016/j.bcra.2024.100189","DOIUrl":"10.1016/j.bcra.2024.100189","url":null,"abstract":"<div><p>In today's corporate environment, Environmental, Social, and Governance (ESG) reports crucially reflect an organization's commitment to sustainability, environmental preservation, and social responsibility. As corporations share these detailed reports, the responsibility to validate and assure adherence to respected ESG benchmarks critically lies with third-party assurance organizations. However, the essential verification process often encounters challenges related to authenticity, credibility, and fairness, underscoring the need for a new solution. The selection of verifiers is a crucial aspect of this process, as their expertise and impartiality directly impact the validity and trustworthiness of the verification. Consequently, “Veri-Green,” an innovative blockchain-based incentive mechanism, has been introduced to improve the ESG data verification process. Considering potential risks in verification systems, such as reputational damage due to oversight or inadvertent approval of inaccurate data, and data security risks involving the management of sensitive organizational information, the verifier selection process needs to be thoroughly considered and designed. Through the utilization of advanced machine learning algorithms, potential verification candidates are precisely identified, followed by the deployment of the Vickrey Clarke Groves (VCG) auction mechanism. This approach ensures the strategic selection of verifiers and cultivates an ecosystem marked by truthfulness, rationality, and computational efficiency throughout the ESG data verification process. In this framework, verifiers are not only encouraged but also properly incentivized, developing a more transparent and equitable verification process, thereby driving the ESG agenda towards a future defined by genuine, impactful corporate responsibility and sustainability.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 2","pages":"Article 100189"},"PeriodicalIF":6.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000022/pdfft?md5=a05aa881600d205edb9fd810828ad931&pid=1-s2.0-S2096720924000022-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140520791","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":"TMAS: A transaction misbehavior analysis scheme for blockchain","authors":"","doi":"10.1016/j.bcra.2024.100197","DOIUrl":"10.1016/j.bcra.2024.100197","url":null,"abstract":"<div><p>Blockchain-based cryptocurrencies, such as Bitcoins, are increasingly popular. However, the decentralized and anonymous nature of these currencies can also be (ab)used for nefarious activities such as money laundering, thus reinforcing the importance of designing tools to effectively detect malicious transaction misbehaviors. In this paper, we propose TMAS, a transaction misbehavior analysis scheme for blockchain-based cryptocurrencies. Specifically, the proposed system includes ten features in the transaction graph, two heuristic money laundering models, and an analysis method for account linkage, which identifies accounts that are distinct but controlled by an identical entity. To evaluate the effectiveness of our proposed indicators and models, we analyze 100 million transactions and compute transaction features, and are able to identify a number of suspicious accounts. Moreover, the proposed methods can be applied to other cryptocurrencies, such as token-based cryptocurrencies (e.g., Bitcoins) and account-based cryptocurrencies (e.g., Ethereum).</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 3","pages":"Article 100197"},"PeriodicalIF":6.9,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000101/pdfft?md5=0bb3bae5cba1c0b9cda4f64742a45a28&pid=1-s2.0-S2096720924000101-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140757228","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":"Secure smart contract-based digital twins for the Internet of Things","authors":"Iakovos Pittaras ,&nbsp;Nikos Fotiou ,&nbsp;Christos Karapapas ,&nbsp;Vasilios A. Siris ,&nbsp;George C. Polyzos","doi":"10.1016/j.bcra.2023.100168","DOIUrl":"10.1016/j.bcra.2023.100168","url":null,"abstract":"<div><p>The proliferation of Internet of Things (IoT) devices that operate unattended providing a multitude of important and often sensitive services highlights the need for seamless interoperability and increased security. We argue that digital twins of IoT devices, with the right design, can enhance the security, reliability, auditability, and interoperability of IoT systems. The salient features of digital twins have made them key elements for the IoT and Industry 4.0. In this paper, we leverage advances in W3C's Web of Things (WoT) standards and distributed ledger technologies (DLTs) to present a novel design of the smart contract-based digital twins with enhanced security, transparency, interoperability, and reliability. We provide two different variations of that general design using two different blockchains (one public and one private, permissioned blockchain), and we present design trade-offs. Furthermore, we introduce an architecture for accessing and controlling IoT devices securely and reliably, providing full auditability, while at the same time using the proposed digital twins as an indirection mechanism (proxy). The proposed architecture leverages the blockchain to offer notable properties, namely,decentralization, immutability, auditability, non-repudiation, availability, and reliability. Moreover, it introduces mass actuation, easier management of IoT devices, and enhanced security to the IoT gateways, enables new business models, and makes consumer devices (vendor-)agnostic.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 1","pages":"Article 100168"},"PeriodicalIF":5.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S209672092300043X/pdfft?md5=0376a47ce6ca0b86a9111441dca241b3&pid=1-s2.0-S209672092300043X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139291335","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":"Towards a lightweight security framework using blockchain and machine learning","authors":"Shereen Ismail ,&nbsp;Muhammad Nouman ,&nbsp;Diana W. Dawoud ,&nbsp;Hassan Reza","doi":"10.1016/j.bcra.2023.100174","DOIUrl":"10.1016/j.bcra.2023.100174","url":null,"abstract":"<div><p>Cyber-attacks pose a significant challenge to the security of Internet of Things (IoT) sensor networks, necessitating the development of robust countermeasures tailored to their unique characteristics and limitations. Various prevention and detection techniques have been proposed to mitigate these attacks. In this paper, we propose an integrated security framework using blockchain and Machine Learning (ML) to protect IoT sensor networks. The framework consists of two modules: a blockchain prevention module and an ML detection module. The blockchain prevention module has two lightweight mechanisms: identity management and trust management. Identity management employs a lightweight Smart Contract (SC) to manage node registration and authentication, ensuring that unauthorized entities are prohibited from engaging in any tasks, while trust management uses a lightweight SC that is responsible for maintaining trust and credibility between sensor nodes throughout the network's lifetime and tracking historical node behaviors. Consensus and transaction validation are achieved through a Verifiable Byzantine Fault Tolerance (VBFT) mechanism to ensure network reliability and integrity. The ML detection module utilizes the Light Gradient Boosting Machine (LightGBM) algorithm to classify malicious nodes and notify the blockchain network if it must make decisions to mitigate their impacts. We investigate the performance of several off-the-shelf ML algorithms, including Logistic Regression, Complement Naive Bayes, Nearest Centroid, and Stacking, using the WSN-DS dataset. LightGBM is selected following a detailed comparative analysis conducted using accuracy, precision, recall, F1-score, processing time, training time, prediction time, computational complexity, and Matthews Correlation Coefficient (MCC) evaluation metrics.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 1","pages":"Article 100174"},"PeriodicalIF":5.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000490/pdfft?md5=d3e04ef409a1e66ba5a5635dc01318e7&pid=1-s2.0-S2096720923000490-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139295793","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":"An overview of Web3 technology: Infrastructure, applications, and popularity","authors":"Renke Huang ,&nbsp;Jiachi Chen ,&nbsp;Yanlin Wang ,&nbsp;Tingting Bi ,&nbsp;Liming Nie ,&nbsp;Zibin Zheng","doi":"10.1016/j.bcra.2023.100173","DOIUrl":"10.1016/j.bcra.2023.100173","url":null,"abstract":"<div><p>Web3, the next generation of the Internet, represents a decentralized and democratized web. Although it has garnered significant public interest and found numerous real-world applications, there is a limited understanding of people's perceptions and experiences with Web3. In this study, we conducted an empirical study to investigate the categories of Web3 applications and their popularity, as well as the potential challenges and opportunities within this emerging landscape. Our research was carried out in two phases. In the first phase, we analyzed 200 popular Web3 projects associated with 10 leading Web3 venture capital firms. In the second phase, we collected and examined code-related data from GitHub and market-related data from blockchain browsers (e.g., Etherscan) for these projects. Our analysis revealed that the Web3 ecosystem can be categorized into two groups, i.e., Web3 infrastructure and Web3 applications, with each consisting of several subcategories or subdomains. We also gained insights into the popularity of these Web3 projects at both the code and market levels and pointed out the challenges in the Web3 ecosystem at the system, developer, and user levels, as well as the opportunities it presents. Our findings contribute to a better understanding of Web3 for researchers and developers, which in turn promotes further exploration and advancement in this innovative field.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"5 1","pages":"Article 100173"},"PeriodicalIF":5.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000489/pdfft?md5=9aa14a7904cbf749ffa73e8e3272e865&pid=1-s2.0-S2096720923000489-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139299917","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}