Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics
The widespread adoption of autonomous driving technology heavily relies on data acquisition and processing, which, while providing an intelligent experience for users, also raises concerns about data security, personal privacy, and data exploitation. The data security of autonomous driving faces cha...
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MDPI AG
2024-12-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/1/6 |
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| author | Yao Xu Jixin Wei Ting Mi Zhihua Chen |
| author_facet | Yao Xu Jixin Wei Ting Mi Zhihua Chen |
| author_sort | Yao Xu |
| collection | DOAJ |
| description | The widespread adoption of autonomous driving technology heavily relies on data acquisition and processing, which, while providing an intelligent experience for users, also raises concerns about data security, personal privacy, and data exploitation. The data security of autonomous driving faces challenges from three aspects: technology, law, and social ethics. Thus, this article adopts interdisciplinary research methods to identify these challenges and provide solutions from diverse disciplinary perspectives. (a) Technologically, issues such as data leakage, storage vulnerabilities, and the risk of re-identifying anonymous data persist; (b) legally, there is an urgent need to clarify the responsible parties and address issues related to outdated data security legislation and legal conflicts arising from cross-border data flows; (c) socially and ethically, the risks of data misuse and the emergence of exploitative contracts have triggered public concerns about data privacy. To address these challenges, this article proposes technical countermeasures such as utilizing diverse Privacy Enhancing Technologies (PETs) to enhance data anonymity, optimizing data encryption techniques, and reinforcing data monitoring and access control management. Legal measures should include establishing a comprehensive data security protection framework, clarifying accountability, and developing standards for the classification and grading of autonomous vehicle data. In the field of social ethics, emphasis is placed on safeguarding the public’s right to know, establishing a transparent system for data use, offering an alternative “data security” solution that allows users to choose between heightened privacy protection and enhanced personalized services, and also advocating ethical data utilization and technological development. By implementing these comprehensive strategies, we aim to establish a secure and barrier-free data protection system for autonomous driving, thereby laying a solid foundation for the widespread adoption of autonomous driving technology. |
| format | Article |
| id | doaj-art-2d0256c204df43e6967a06f8921f3efe |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | World Electric Vehicle Journal |
| spelling | doaj-art-2d0256c204df43e6967a06f8921f3efe2025-01-24T13:52:44ZengMDPI AGWorld Electric Vehicle Journal2032-66532024-12-01161610.3390/wevj16010006Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social EthicsYao Xu0Jixin Wei1Ting Mi2Zhihua Chen3Civil and Commercial Law, Chongqing University, No. 174 Shazhengjie, Shapingba, Chongqing 400044, ChinaFaculty of Law, University of Zürich, Rämistrasse 71, 8006 Zürich, SwitzerlandCenter for Legal Information of ECUPL, East China University of Political Science and Law, Wan Hang Du Road 1575, Shanghai 200042, ChinaFaculty of Law, Wuhan University, Bayi Road 299, Wuhan 430072, ChinaThe widespread adoption of autonomous driving technology heavily relies on data acquisition and processing, which, while providing an intelligent experience for users, also raises concerns about data security, personal privacy, and data exploitation. The data security of autonomous driving faces challenges from three aspects: technology, law, and social ethics. Thus, this article adopts interdisciplinary research methods to identify these challenges and provide solutions from diverse disciplinary perspectives. (a) Technologically, issues such as data leakage, storage vulnerabilities, and the risk of re-identifying anonymous data persist; (b) legally, there is an urgent need to clarify the responsible parties and address issues related to outdated data security legislation and legal conflicts arising from cross-border data flows; (c) socially and ethically, the risks of data misuse and the emergence of exploitative contracts have triggered public concerns about data privacy. To address these challenges, this article proposes technical countermeasures such as utilizing diverse Privacy Enhancing Technologies (PETs) to enhance data anonymity, optimizing data encryption techniques, and reinforcing data monitoring and access control management. Legal measures should include establishing a comprehensive data security protection framework, clarifying accountability, and developing standards for the classification and grading of autonomous vehicle data. In the field of social ethics, emphasis is placed on safeguarding the public’s right to know, establishing a transparent system for data use, offering an alternative “data security” solution that allows users to choose between heightened privacy protection and enhanced personalized services, and also advocating ethical data utilization and technological development. By implementing these comprehensive strategies, we aim to establish a secure and barrier-free data protection system for autonomous driving, thereby laying a solid foundation for the widespread adoption of autonomous driving technology.https://www.mdpi.com/2032-6653/16/1/6autonomous drivingdata securitydata anonymizationcross-border flow of datadata classificationdata tiering |
| spellingShingle | Yao Xu Jixin Wei Ting Mi Zhihua Chen Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics World Electric Vehicle Journal autonomous driving data security data anonymization cross-border flow of data data classification data tiering |
| title | Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics |
| title_full | Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics |
| title_fullStr | Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics |
| title_full_unstemmed | Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics |
| title_short | Data Security in Autonomous Driving: Multifaceted Challenges of Technology, Law, and Social Ethics |
| title_sort | data security in autonomous driving multifaceted challenges of technology law and social ethics |
| topic | autonomous driving data security data anonymization cross-border flow of data data classification data tiering |
| url | https://www.mdpi.com/2032-6653/16/1/6 |
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