基于雾计算的群智感知车联网隐私保护研究

Internet of vehicles based on crowd sensing provides crowd sensing services to vehicles, among which kinds of privacy issues happens. Privacy disclosure will seriously threaten the security of vehicles, and thus solving privacy problems becomes the prerequisites for the extensive application of the Internet of vehicles. However, most existing solutions are based on traditional architecture, which causes low real-time response and inefficient data acquisition, therefore the privacy problems can not be solved completely. This research aims to address privacy issues by providing a systematic research into the framework, the model and the protocols. It plans to achieve three aims: (1) propose a hierarchical framework of privacy protection for the Internet of vehicles based on crowd sensing; (2) formalize a fine-grained privacy protection strategic model; (3) design two kinds of practical protocols for Internet of vehicles. The research aims to solve the following three problems: (1) the metric problem of the interplay among various privacy elements; (2) the formalization problem of the privacy protection strategy model; (3) the optimization problem of the execution efficiency and the security of privacy protection protocols based on cryptographic.algorithms. This research will provide a theoretical basis and technical reference for solving the privacy problem in Internet of vehicles based on crowd sensing, and lay a foundation for the subsequent research of the privacy protection and security of both the Internet of vehicles and Intelligent Transportation System.

群智感知车联网利用移动群智感知特性为车辆用户提供感知服务，在此过程中存在各种隐私泄露问题。隐私泄露会给用户带来严重的安全隐患，因此解决隐私保护问题成为群智感知车联网得以广泛应用的前提。由于当前研究基于传统车联网架构带来的实时性差、数据获取效率低的局限性，使得群智感知车联网隐私保护问题无法根本解决。本课题从基于雾计算的车联网架构出发，对群智感知车联网隐私保护框架、模型、协议进行研究。拟实现以下研究目标：①提出一个统一结构的群智感知车联网隐私保护框架；②设计一个形式化的细粒度隐私保护策略模型；③设计两个实用的隐私保护协议。拟重点解决：①各种隐私元素相互影响的度量问题；②细粒度隐私保护策略模型的形式化问题。②基于密码算法的隐私保护协议执行效率和安全性的优化问题。课题的开展将为群智感知车联网隐私保护问题的解决提供重要的理论依据和技术参考，为后续车联网和智能交通系统隐私保护问题研究奠定基础。

针对车联网群智感知场景下存在的各种隐私泄露问题，研究了群智感知车联网隐私保护框架、模型、协议和相关核心算法。主要研究内容包括：①基于雾计算的分布式隐私保护框架：通过区块链技术搭建了适用于不同车联网群智感知场景下的隐私保护框架、模型；②细粒度隐私保护策略模型：通过反向拍卖、多维影响因子、匿名级别划分等技术，提出了满足个性化隐私需求的隐私保护策略；③车位共享系统中的隐私保护协议：结合市场设计理论和区块链、隐私货币技术，提出了针对车位共享者的隐私保护协议。④具有隐私保护特性的车联网群智感知激励机制：提出了基于零知识证明技术的隐私保护方案，并基于区块链智能合约给出了智能激励方案，在仿真环境下进行了方案测试。⑤针对环签名等匿名技术在车联网环境下存在的影响其匿名性的节点选择问题和签名长度过大问题，研究了相应的节点选择算法和轻量级方案的构造方法，确保这类密码技术在车联网环境下的匿名性和适用性。综合上述研究内容，本项目的开展为群智感知车联网隐私保护问题提供了安全的隐私保护框架和模型，解决了部分车联网群智感知场景下的隐私保护问题，为有相同隐私保护需求的车联网场景提供了重要的理论依据和技术参考。