汽车领域隐私保护计算研究综述

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Nergiz Yuca, Nikolay Matyunin, Ektor Arzoglou, Nikolaos Athanasios Anagnostopoulos, Stefan Katzenbeisser
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引用次数: 0

摘要

随着汽车互联和自动化程度的提高,它们会积累和管理各种个人数据,从而在数据共享和处理过程中保护隐私,这是一个关键挑战。本调查回顾了安全多方计算(MPC)和同态加密(HE)在汽车领域解决这些隐私问题的应用。首先,我们通过调查解决不同汽车环境(如基于位置的服务、移动基础设施、交通管理等)中隐私问题的现有工作,确定了这些技术隐私敏感用例的范围。然后,我们详细回顾了最近使用MPC和HE作为这些用例解决方案的工作。我们的调查强调了这些隐私保护技术在汽车环境中的适用性,同时也指出了当前研究领域的挑战和差距。这项工作旨在为这一新兴领域提供一个清晰而全面的概述,并鼓励在这一领域的进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Privacy-Preserving Computing in the Automotive Domain
As vehicles become increasingly connected and autonomous, they accumulate and manage various personal data, thereby presenting a key challenge in preserving privacy during data sharing and processing. This survey reviews applications of Secure Multi-Party Computation (MPC) and Homomorphic Encryption (HE) that address these privacy concerns in the automotive domain. First, we identify the scope of privacy-sensitive use cases for these technologies, by surveying existing works that address privacy issues in different automotive contexts, such as location-based services, mobility infrastructures, traffic management, etc. Then, we review recent works that employ MPC and HE as solutions for these use cases in detail. Our survey highlights the applicability of these privacy-preserving technologies in the automotive context, while also identifying challenges and gaps in the current research landscape. This work aims to provide a clear and comprehensive overview of this emerging field and to encourage further research in this domain.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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