汽车工业
计算机科学
同态加密
范围(计算机科学)
领域(数学分析)
钥匙(锁)
领域(数学)
加密
计算机安全
信息隐私
工作(物理)
新兴技术
数据共享
数据科学
设计隐私
大数据
云计算
隐私软件
信息共享
作者
Nergiz Yuca,Nikolay Matyunin,Ektor Arzoglou,Nikolaos Athanasios Anagnostopoulos,Stefan Katzenbeisser
摘要
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, and so on. 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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