检索结果-内蒙古大学图书馆

A Trusted Data privacy computing Method for Vehicular Ad Hoc Networks Based on Homomorphic Encryption and DAG Blockchain

引用

IEEE INTERNET OF THINGS JOURNAL 2025年第6期12卷 6621-6632页

作者： Jiang, Wenxian Tao, Jun Guan, Zhenglei Southeast Univ Sch Cyber Sci & Engn Nanjing 211189 Peoples R China Huaqiao Univ Coll Comp Sci & Technol Xiamen 361000 Peoples R China

Recently, vehicular ad hoc networks (VANETs) have garnered significant attention in the industry, thanks to their distinctive characteristics of mobility and real-time capabilities. In order to protect the privacy of data sharing in VANETs, a privacy computing scheme based on homomorphic encryption and blockchain has been proposed. First, the Paillier algorithm of homomorphic encryption is used to encrypt the data, making it available but not invisible to ensure the security of the data. Second, the data structure of a directed acyclic graph (DAG) is applied to replace the chain structure so that it can be processed in parallel and reduce the delay time of transmission confirmation. Finally, a single point cluster is set up in the Bigchain database, and Docker virtual technology is used to simulate the high dynamic and high load environment of VANETs, so as to verify the computational efficiency and security of the proposed scheme. The experimental results show that the privacy computing scheme combining homomorphic encryption and DAG blockchain not only eliminates the need for repeated encryption and decryption in the communication process but also reduces the computational cost associated with private data. Compared with traditional chain blockchain, this scheme achieves a comprehensive delay reduction of 68.51% and shortens the average confirmation time by 85.73%, effectively meeting the high-performance requirements of VANETs.

关键词： Blockchains Homomorphic encryption Data privacy Security privacy Public key Protection Vehicle dynamics Throughput Stability analysis Blockchain directed acyclic graph (DAG) homomorphic encryption privacy computing vehicular ad-hoc networks (VANETs)

来源：评论

学校读者我要写书评

暂无评论

Bidirectional utilization of blockchain and privacy computing: Issues, progress, and challenges

引用

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2024年 222卷

作者： Zhang, Hongwei Fan, Wei Wang, Jinsong Tianjin Univ Technol Sch Comp Sci & Engn Tianjin 300384 Peoples R China Tianjin Key Lab Intelligence Comp & Novel Software Tianjin 300384 Peoples R China Natl Engn Lab Comp Virus Prevent & Control Techno Tianjin 300457 Peoples R China

With the rapid development of information technology and the increasing popularity of personalized services, the flow of users' personal information in the Internet is inevitable between different platforms and applications, which greatly affects the trust relationship in the digital society. In recent years, an increasing number of researchers have been dedicated to exploring the applications of blockchain and privacy computing technologies in the process of data value release. Scholars have discovered that the combination of the two technologies can alleviate many pain points of each other. Specifically, privacy computing is a computational theory and method for protecting privacy of information throughout its lifecycle. privacy computing enables the processing, analysis, and computation of data while preserving the confidentiality of the original information. Nevertheless, challenges related to data ownership and benefit distribution impede the establishment of a fair and effective collaborative environment among multiple parties, thereby restricting its further practical development. On the other hand, blockchain is a technology for establishing a trusted platform among mutually untrusted parties, characterized by decentralization, immutability, traceability, and incentive mechanisms. However, blockchain also faces security issues such as transparency of on-chain data and lack of protection in smart contract execution environments. Therefore, this paper aims to comprehensively analyze and explore the integration of blockchain and privacy computing from both perspectives, focusing on bidirectional utilization. We systematically categorize and summarize relevant literature in this field, employing problem-oriented approaches. Finally, we identify the existing challenges and propose potential improvement methods in this field.

关键词： Blockchain privacy computing Bidirectional utilization Secure multi-party computation Trusted execution environment Federated learning

来源：评论

学校读者我要写书评

暂无评论

Research on interconnection technology of heterogeneous platforms for privacy computing for energy big data 3

Research on interconnection technology of heterogeneous plat...

引用

3rd International Conference on Energy and Power Engineering, Control Engineering (EPECE)

作者： Zhai, Yujia Huang, Xiuli Yu, Pengfei State Grid Smart Grid Res Inst Co Ltd State Grid Lab Power Cyber Secur Protect & Monito Nanjing Peoples R China

ISBN: (纸本)9798350366105;9798350366099

Energy data, especially power data, has the advantages of covering a wide range of industries, high value density, and good accuracy, relying on energy big data can widely describe all kinds of terminal production and life activities. However, the privacy computing platforms of various vendors often adopt different technical architectures and algorithm protocols in the early implementation process, which makes the implementation of various platforms have great differences, resulting in the direct interconnection between heterogeneous privacy computing platforms of various organizations. Aiming at the interoperability needs and problems of energy big data privacy computing platforms with different technical architectures, this paper decouple the management plane and data plane of the privacy computing platform, and in accordance with the principle of business priority, proposes a new privacy computing interconnection model of "unified business collaboration component + flexible configuration algorithm engine" suitable for energy big data. Through the design of the east-west and North-South interface framework of the privacy computing platform and the security access principle of the algorithm engine, the whole process control, cross-platform interconnection, and internal and external network penetration modeling and analysis of energy big data collaboration with the outside world are realized, which meets the key data security protection requirements of the State Grid such as distributed computing and storage of data inside and outside the platform. It is of great significance to promote energy big data to empower external institutions such as governments, banks and operators.

关键词： privacy computing energy big data cross-heterogeneous platforms connectivity technologies

来源：评论

学校读者我要写书评

暂无评论

PMHE: a wearable medical sensor assisted framework for health care based on blockchain and privacy computing

引用

JOURNAL OF CLOUD computing-ADVANCES SYSTEMS AND APPLICATIONS 2022年第1期11卷 1-17页

作者： Zhao, Jindong Wang, Wenshuo Wang, Dan Wang, Xuan Mu, Chunxiao Yantai Univ Sch Comp & Control Engn Yantai 264005 Peoples R China

Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy preserving framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged;Besides, it uses fully homomorphic encryption method to design disease prediction models implemented by smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping;smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too. So, privacy and security issues caused by platform data leakage are avoided. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.

关键词： Blockchain Homomorphic encryption Smart contracts privacy computing Smart medical

来源：评论

学校读者我要写书评

暂无评论

Application of privacy computing to Smart Grid Data Sharing Platform 2

Application of Privacy Computing to Smart Grid Data Sharing ...

引用

2nd Asian Conference on Frontiers of Power and Energy (ACFPE)

作者： Jia, Ning Gao, QiaoMei Liu, YongMei Meng, Hao Liu, ShuQing Yi, FengChao Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China Inner Mongolia Univ Finance Dept Hohhot Peoples R China Inner Mongolia IEDS Co Ltd Tech Res Inst Hohhot Peoples R China

ISBN: (纸本)9798350303896

Data, as an emerging factor of production, is profoundly changing the traditional mode of production and at the same time giving rise to the need for a data-centered digital economy. Currently, data sharing between governments and enterprises as well as between enterprises is being rapidly explored. This study focuses on the big data information sharing service platform of an electric power company, which mainly buttresses government departments such as the Discipline Inspection and Supervision Commission of the Autonomous Region, the Development and Reform Commission, and the Bureau of Energy, providing them with information such as user profiles, electricity consumption, meter readers, and payment status of the relevant personnel houses, as well as providing electric power data services for government agencies and other units. However, in the process of data sharing, the risks of low-cost data replication, data leakage, and personal privacy violation come to the fore. Therefore, how to ensure data availability while maintaining data security and privacy protection has become an urgent challenge for data sharing today. The platform uses privacy computing technology to solve the problem of sharing data elements, realizes the goal of "original data not out of domain" in the flow mode, ensures the "available and invisible" state of data in the process of sharing and fusion, realizes the transfer of data value only, breaks the information chimney between departments and regions, and reduces the risk of violation of personal privacy. It has broken the information chimney between departments and regions, and achieved real information sharing.

关键词： Data Sharing privacy computing State Secrets Algorithms Data Elements Smart Grids

来源：评论

学校读者我要写书评

暂无评论

Research and application of power blockchain data sharing technology based on privacy computing 3

Research and application of power blockchain data sharing te...

引用

3rd International Conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Shi, Ying Wang, Lixing Ao, Jin Song, Jie Li, Qian Zhang, Xuesen State Grid Jilin Electric Power Company Co. Ltd Jilin China Co. Ltd. Beijing China

ISBN: (纸本)9798350352658

A new type of power system gathers large-scale energy and related data. This paper builds a blockchain power data trusted sharing platform prototype system with independent intellectual property rights to provide a trusted data basis for data sharing, data security, data privacy protection and other functions, explore the potential value of power data, and standardize and standardize the power data market. Based on the key technology of blockchain data management, it realizes the trusted sharing of data side chain support business, ensures the safe interaction of supply chain data, further releases the potential energy of service chain industry, optimizes the industrial environment, and promotes the value-added realization of power data assets. © 2024 IEEE.

关键词： Blockchain Data sharing Power service data privacy computing

来源：评论

学校读者我要写书评

暂无评论

privacy computing meets metaverse: Necessity, taxonomy and challenges

引用

AD HOC NETWORKS 2024年 158卷

作者： Chen, Chuan Li, Yuecheng Wu, Zhenpeng Mai, Chengyuan Liu, Youming Hu, Yanming Kang, Jiawen Zheng, Zibin Sun Yat Sen Univ Sch Comp Sci & Engn GuangZhou Peoples R China Sun Yat Sen Univ Sch Software Engn ZhuHai Peoples R China Guangdong Univ Technol Sch Automat GuangZhou Peoples R China

Metaverse, the core of the next -generation Internet, is a computer -generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and datasensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is becoming more and more sophisticated and widely used in various fields such as social, tourism, industry and economy. However, the high level of interaction with the real world also means a huge risk of privacy leakage both for individuals and enterprises, which has hindered the wide deployment of metaverse. Then, it is inevitable to apply privacy computing techniques in the framework of metaverse, which is a current research hotspot. In this paper, we conduct comprehensive research on the necessity, taxonomy and challenges when privacy computing meets metaverse. Specifically, we first introduce the underlying technologies and various applications of metaverse, on which we analyze the challenges of data usage in metaverse, especially data privacy. Next, we review and summarize state-of-theart solutions based on federated learning, differential privacy, homomorphic encryption, and zero -knowledge proofs for different privacy problems in metaverse. Finally, we show the current security and privacy challenges in the development of metaverse and provide open directions for building a well -established privacy -preserving metaverse system. For easy access and reference, we integrate the related publications and their codes into a GitHub repository: https://***/6lyc/***.

关键词： Metaverse Data privacy privacy computing Mobile edge computing Blockchain Extended reality

来源：评论

学校读者我要写书评

暂无评论

Public Credit Data Circulation and Sharing based on privacy computing

Public Credit Data Circulation and Sharing based on Privacy ...

引用

2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Zhang, Fengna Liu, Renzhong Harbin University of Commerce School of Finance Harbin China Harbin Finance University Financial Supervision and Financial Risk Prevention Research Center Harbin China

ISBN: (纸本)9798350375442

In the digital age, public credit data is crucial for financial stability and business integrity but is hindered by privacy concerns and data silos. This study proposes an innovative privacy computing model integrating differential privacy, homomorphic encryption, and federated learning to enhance data sharing while protecting privacy. Differential privacy masks data by adding noise, homomorphic encryption allows computations on encrypted data, and federated learning enables collaborative model improvement without data exchange. Experiments show this model effectively balances privacy protection and data usability. For example, varying the differential privacy parameter ϵ from 0.1 to 10 adjusted the trade-off between data privacy and accuracy. The findings suggest that while the model significantly improves data flow efficiency and prediction accuracy, it also maintains robust data privacy. This research advances the application of privacy-preserving technologies in public credit data management, offering a foundation for further exploration in larger and more diverse applications. © 2024 IEEE.

关键词： data flow data sharing privacy computing public credit data

来源：评论

学校读者我要写书评

暂无评论

An Industrial Digital Financial Application Platform based on privacy computing 24

An Industrial Digital Financial Application Platform based o...

引用

Proceedings of the 2024 the 12th International Conference on Information Technology (ICIT)

作者： Xiaobin Zhang Peng Chen Chongsong You Bin Liu Meilin Huang CCCC (Xiamen) E-commerce Co. Ltd Xiamen China

ISBN: (纸本)9798400717376

In the digital economy era, data information has become an indispensable production factor and the core asset of enterprises. Therefore, the data privacy protection issue is highlighted. Recently, privacy computing technology has become the focus of both academic and industry. The property of data that can be easily replicated leads an exposed information problem. We aim to build a safe, efficient, active and well-established industrial digital financial application platform for privacy computing. First, the user’s preferences, interests and behaviors are generated based on the analysis of their browsing history. Then, add noise or disturbance to the data, after that, the data is processed through the differential privacy algorithm. This platform contains modules such as data acquisition, data encryption and desensitization, differential privacy protection and so on. The platform utilizes a low-coupling and modular design approach. As a result, the data is available but invisible, and the ownership of data is clear. The data sharing is achieved on the premise of security and privacy.

关键词： privacy computing

来源：评论

学校读者我要写书评

暂无评论

The Failure and Response of Risk Prevention Regulations: Taking privacy computing as an Example

引用

Open Journal of Social Sciences 2023年 11卷 533-550页

作者： Xinhui Liu School of Economic Law Shanghai University of Politics and Law Shanghai China

Against the backdrop of the continuous development of the data economy and the widespread application of algorithm technology, the protection of data security and privacy has increasingly become a concern for countries, society, enterprises, and individuals. As a new algorithm technology, privacy computing is known as the “optimal solution for data security and privacy protection” due to its “available and invisible” technical characteristics and wide applicability. However, the issue of immature privacy computing technology is becoming increasingly prominent, and the deep-seated contradiction between data utilization and data protection cannot be fundamentally resolved, which seriously restricts the practicality of privacy computing application scenarios. The risks faced by privacy computing not only have their own technological flaws, but also traditional risk prevention and regulation methods still have incompatibilities in addressing compliance issues in privacy computing. There are a series of risks such as unclear legal status of participating methods, high cost of algorithm interpretation, and inaccurate calculation results. Resolving these risks requires starting from the current development status of privacy computing. Targeted modifications and improvements should be made to the application difficulties of China’s risk regulation methods for privacy computing, in order to explore the establishment of a data governance compliance system to solve algorithmic problems and promote the practicality of new algorithmic technologies represented by privacy computing.

关键词： privacy computing Data Security Technical Compliance China

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：