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FADSF:A data sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

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Computers, Materials & Continua 2024年第8期80卷 2351-2362页

作者： Yan Sun Caiyun Liu Jun Li Yitong Liu data Security Institute China Industrial Control Systems Cyber Emergency Response TeamBeijing100040China

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage *** data of ICV(intelligent connected vehicles)is the key to organically maximizing their ***,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are *** study proposes FADSF(Fuzzy Anonymous data Share Frame),an automobile data sharing scheme based on *** data holder publishes the shared data information and forms the corresponding label storage on the *** data demander browses the data directory information to select and purchase data assets and verify *** data demander selects and purchases data assets and verifies them by browsing the data directory ***,this paper designs a data structure data Discrimination Bloom Filter(DDBF),making complaints about illegal *** the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing *** this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

关键词： Blockchain connected vehicles data sharing smart contracts credible traceability

Blockchain-Enabled Federated Learning for Privacy-Preserving Non-IID data sharing in Industrial Internet

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Computers, Materials & Continua 2024年第8期80卷 1967-1983页

作者： Qiuyan Wang Haibing Dong Yongfei Huang Zenglei Liu Yundong Gou School of Electrical and Information Engineering Hunan Institute of TechnologyHengyang421002China

sharing data while protecting privacy in the industrial Internet is a significant *** machine learning methods require a combination of all data for training;however,this approach can be limited by data availability and privacy *** learning(FL)has gained considerable attention because it allows for decentralized training on multiple local ***,the training data collected by data providers are often non-independent and identically distributed(non-IID),resulting in poor FL *** paper proposes a privacy-preserving approach for sharing non-IID data in the industrial Internet using an FL approach based on blockchain *** overcome the problem of non-IID data leading to poor training accuracy,we propose dynamically updating the local model based on the divergence of the global and local *** approach can significantly improve the accuracy of FL training when there is relatively large *** addition,we design a dynamic gradient clipping algorithm to alleviate the influence of noise on the model accuracy to reduce potential privacy leakage caused by sharing model ***,we evaluate the performance of the proposed scheme using commonly used open-source image *** simulation results demonstrate that our method can significantly enhance the accuracy while protecting privacy and maintaining efficiency,thereby providing a new solution to data-sharing and privacy-protection challenges in the industrial Internet.

关键词： Federated learning data sharing non-IID data differential privacy blockchain

Privacy-preserving pathological data sharing among multiple remote parties

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BLOCKCHAIN-RESEARCH AND APPLICATIONS 2024年第3期5卷 67-77页

作者： Wu, Wei Chen, Fulong Wang, Taochun Xie, Dong Zhao, Chuanxin Wang, Chao Tang, Detao Li, Jingtao Zhang, Ji Anhui Normal Univ Anhui Prov Key Lab Network & Informat Secur Wuhu 241002 Peoples R China Univ Southern Queensland Toowoomba Qld 4350 Australia

The sharing of pathological data is highly important in various applications, such as remote diagnosis, graded diagnosis, illness treatment, and specialist system development. However, ensuring reliable, secure, privacy- preserving, and efficient sharing of pathological data poses significant challenges. This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing. Additionally, it employs conditional proxy re-encryption (C-PRE) and public key encryption with equality test technology to control the scope and preserve the privacy of shared data. To assess the practicality of our solution, we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics. We also compared the solution with relevant schemes. The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios.

关键词： Digital remote pathology Conditional proxy re-encryption Blockchain data storage data sharing PROXY RE-ENCRYPTION

A General Framework for Intelligent IoT data Acquisition and sharing in an Untrusted Environment Based on Blockchain

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China Communications 2024年第3期21卷 137-148页

作者： Lu Yin Xue Yongtao Li Qingyuan Wu Luocheng Li Taosen Yang Peipei Zhu Hongbo College of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing 210003China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China Research Institute of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Bell Honors School Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Automation Nanjing University of Posts and TelecommunicationsNanjing 210023China

Traditional Io T systems suffer from high equipment management costs and difficulty in trustworthy data sharing caused by *** provides a feasible research direction to solve these problems. The main challenge at this stage is to integrate the blockchain from the resourceconstrained Io T devices and ensure the data of Io T system is credible. We provide a general framework for intelligent Io T data acquisition and sharing in an untrusted environment based on the blockchain, where gateways become Oracles. A distributed Oracle network based on Byzantine Fault Tolerant algorithm is used to provide trusted data for the blockchain to make intelligent Io T data trustworthy. An aggregation contract is deployed to collect data from various Oracle and share the credible data to all on-chain users. We also propose a gateway data aggregation scheme based on the REST API event publishing/subscribing mechanism which uses SQL to achieve flexible data aggregation. The experimental results show that the proposed scheme can alleviate the problem of limited performance of Io T equipment, make data reliable, and meet the diverse data needs on the chain.

关键词： blockchain data sharing Internet of Things Oracle

Scalable and Privacy-Preserving data sharing Based on Blockchain

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Journal of Computer Science & Technology 2018年第3期33卷 557-567页

作者： Bao-Kun Zheng Lie-Huang Zhu Meng Shen Feng Gao Chuan Zhang Yan-Dong Li Jing Yang School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China School of Information Management for Law China University of Political Science and Law Beijing 102249 China

With the development of network technology and cloud computing, data sharing is becoming increasingly popular, and many scholars have conducted in-depth research to promote its flourish. As the scale of data sharing expands, its privacy protection has become a hot issue in research. Moreover, in data sharing, the data is usually maintained in multiple parties, which brings new challenges to protect the privacy of these multi-party data. In this paper, we propose a trusted data sharing scheme using blockchain. We use blockchain to prevent the shared data from being tampered, and use the Paillier cryptosystem to realize the confidentiality of the shared data. In the proposed scheme, the shared data can be traded, and the transaction information is protected by using the （p, t）-threshold Paillier cryptosystem. We conduct experiments in cloud storage scenarios and the experimental results demonstrate the efficiency and effectiveness of the proposed scheme.

关键词： data sharing privacy-preserving cloud computing blockchain Paillier cryptosystem

Privacy-Preserving data sharing in Cloud Computing

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Journal of Computer Science & Technology 2010年第3期25卷 401-414页

作者：王慧 Department of Computer Science Stevens Institute of Technology Castle Point on Hudson

Storing and sharing databases in the cloud of computers raise serious concern of individual privacy. We consider two kinds of privacy risk： presence leakage, by which the attackers can explicitly identify individuals in （or not in） the database, and association leakage, by which the attackers can unambiguously associate individuals with sensitive information. However, the existing privacy-preserving data sharing techniques either fail to protect the presence privacy or incur considerable amounts of information loss. In this paper, we propose a novel technique, Ambiguity, to protect both presence privacy and association privacy with low information loss. We formally define the privacy model and quantify the privacy guarantee of Ambiguity against both presence leakage and association leakage. We prove both theoretically and empirically that the information loss of Ambiguity is always less than the classic generalization-based anonymization technique. We further propose an improved scheme, PriView, that can achieve better information loss than Ambiguity. We propose efficient algorithms to construct both Ambiguity and PriView schemes. Extensive experiments demonstrate the effectiveness and efficiency of both Ambiguity and PriView schemes.

关键词： privacy data sharing anonymity utility cloud computing

Blockchain-based multiple groups data sharing with anonymity and traceability

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Science China(Information Sciences) 2020年第3期63卷 7-19页

作者： Hui HUANG Xiaofeng CHEN Jianfeng WANG State Key Laboratory of Integrated Service Networks (ISN) Xidian University College of Computer Minnan Normal University

Group data sharing enables information sharing between multiple parties for cooperative purposes. However, the existing schemes only consider scenarios in which all parties in the same organization want to share data. Achieving secure data sharing between users of different groups is also a relevant research issue. In this paper, we propose a blockchain-based data sharing scheme for multiple groups with anonymity and traceability. Owing to the consortium blockchain technique, any user in the system can easily verify the validity of the shared data without interacting with a third-party auditor. Additionally, the proposed scheme can not only enable data sharing between different groups with enhanced security anonymously but also achieve traceability and non-frameability.

关键词： multiple groups data sharing blockchain anonymity traceability

An intelligent and privacy-enhanced data sharing strategy for blockchain-empowered Internet of Things

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Digital Communications and Networks 2022年第5期8卷 636-643页

作者： Qinyang Miao Hui Lin Jia Hu Xiaoding Wang College of Computer and Cyber Security Fujian Normal UniversityFuzhou350117China Engineering Research Center of Cyber Security and Education Informatization Fujian Province UniversityFuzhou350117China University of Exeter EX44RN ExeterUK

With the development of the Internet of Things(IoT),the massive data sharing between IoT devices improves the Quality of Service(QoS)and user experience in various IoT ***,data sharing may cause serious privacy leakages to data *** address this problem,in this study,data sharing is realized through model sharing,based on which a secure data sharing mechanism,called BP2P-FL,is proposed using peer-to-peer federated learning with the privacy protection of data *** addition,by introducing the blockchain to the data sharing,every training process is recorded to ensure that data providers offer high-quality *** further privacy protection,the differential privacy technology is used to disturb the global data sharing *** experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications.

关键词： data sharing Federated learning Blockchain Privacy protection IoT

Evolutionary privacy-preserving learning strategies for edge-based IoT data sharing schemes

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数字通信与网络:英文版 2023年第4期9卷 906-919页

作者： Yizhou Shen Shigen Shen Qi Li Haiping Zhou Zongda Wu Youyang Qu Department of Computer Science and Engineering Shaoxing UniversityShaoxing312000China School of Computer Science and Informatics Cardiff UniversityCardiffCF243AAUnited Kingdom School of Information Engineering Huzhou UniversityHuzhou 313000ZhejiangChina School of Information Technology Deakin UniversityBurwoodVIC3125Australia

The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data *** generated data is collected and shared using edge-based IoT structures at a considerably high ***,the data-sharing privacy exposure issue is increasingly intimidating when IoT devices make malicious requests for filching sensitive information from a cloud storage system through edge *** address the identified issue,we present evolutionary privacy preservation learning strategies for an edge computing-based IoT data sharing *** particular,we introduce evolutionary game theory and construct a payoff matrix to symbolize intercommunication between IoT devices and edge nodes,where IoT devices and edge nodes are two parties of the *** devices may make malicious requests to achieve their goals of stealing ***,edge nodes should deny malicious IoT device requests to prevent IoT data from being *** dynamically adjust their own strategies according to the opponent's strategy and finally maximize the *** upon a developed application framework to illustrate the concrete data sharing architecture,a novel algorithm is proposed that can derive the optimal evolutionary learning ***,we numerically simulate evolutionarily stable strategies,and the final results experimentally verify the correctness of the IoT data sharing privacy preservation ***,the proposed model can effectively defeat malicious invasion and protect sensitive information from leaking when IoT data is shared.

关键词： Privacy preservation Internet of things Evolutionary game data sharing Edge computing