Abstract: Transportation, as a core component of social infrastructure, is closely tied to the data resources within information systems. China, however, continued to face multifaceted challenges to transportation data security. In response to practical needs for protection in this domain, national authorities and industry organizations had already adopted measures in law and regulation, technical protection, and security monitoring. Focusing on the innovative application of Privacy-Enhancing Technologies (PETs) for intelligent transportation data protection, three core technological innovation pathways were systematically reviewed. In the identity-authentication dimension, a distributed authentication framework based on blockchain and zero-knowledge proofs was examined, and system robustness was enhanced by eliminating single points of failure. For access control, a dual-policy attribute-based encryption (DP-ABE) model supporting dynamic revocation was constructed and integrated with fog computing to realize bidirectional policy matching at the data-source and access ends. At the end-to-end encrypted communication layer, the Signal protocol was improved for resistance to quantum attacks and a communication protocol for intelligent transportation terminals was designed. During data processing and analysis, privacy-preserving computation mechanisms were introduced to guarantee that data are “usable but not visible” in federated modeling and collaborative computation, thereby addressing the core tension between extracting value from transportation data and protecting privacy.

Key words: Keywords: Transportation data, Security protection, Decentralized identity authentication, Fine-grained access control, End-to-end encryption, Privacy Computing

摘要： 交通运输领域作为社会基础设施的核心组成部分，其发展与信息化系统中的数据资源紧密相连。然而，我国仍面临来自多方面的交通数据安全挑战。面对该领域数据安全防护的现实需求，目前国家层面、行业内的企事业单位已经从法律法规、技术防护及安全监测等方面采取了相应的措施。聚焦隐私增强技术（Privacy-Enhancing Technologies, PETs）在智能交通数据安全防护中的创新应用，系统梳理了三大核心技术的创新路径：在身份认证领域，基于区块链与零知识证明的分布式认证框架，通过消除单点故障提升系统鲁棒性；在访问控制维度，构建支持动态撤销的双策略属性基加密（DP-ABE）模型，结合雾计算实现数据源端与访问端的双向策略匹配；端到端加密通信层面，改进Signal协议的抗量子攻击能力，设计交通智能终端通信协议；在数据处理与分析阶段，引入隐私计算机制，确保数据在联合建模与协同计算过程中的“可用不可见”，解决交通数据价值挖掘与隐私保护间的核心矛盾。

关键词: 交通数据, 安全防护, 去中心化身份认证, 细粒度访问控制, 端到端加密, 隐私计算