车联网环境下的隐私安全度量方法

Privacy Metric Review of Internet of Vehicles

摘要:

阐释了车联网的特点、隐私特性和隐私攻击等，从身份隐私、位置隐私、数据隐私三个方面阐述了不同类型隐私在隐私保护方面的特点和需求，并梳理了针对不同隐私类型的隐私保护关键技术和方法演进；在此基础上，研究了不同类型隐私的隐私度量代表性方案、理论模型、度量难题等方面，归纳了涉及车联网环境下隐私度量的8个关键属性，并讨论了相关的32个度量指标。最后，总结了车联网隐私度量的未来研究方向及挑战。

Abstract:

This paper first reviews the privacy backgrounds especially the Internet of Vehicle （IoV）characteristics， privacy features and common privacy leakage attacks. Then， it elaborates the characteristics and needs of different types of privacy in terms of identity privacy， location privacy and data privacy as well as the key privacy protection technologies and methodological evolutions for different privacy types . On this basis， the representative privacy metrics schemes， theoretical models， and metrics challenges for different types of privacy are studied in depth across multiple privacy domains. Furthermore， 8 key attributes and 32 indicators of privacy metrics in IoV are summarized. Finally， a discussion is also made on the future research directions and challenges of privacy metrics.