针对车联网中 Mix-zone 方案灵活性低以及隐私保护程度对用户缺乏透明度的问题,提出一种交通自适应的动态Mix-zone创建方法,可以根据道路交通状况为车辆动态创建Mix-zone,随时随地为车辆创建Mix-zone进行假名更换,建立基于身份和位置的隐私保护;提出对 Mix-zone 进行隐私分级的联合熵度量模型,可通过归一化的定量计算结果度量 Mix-zone 达到当前区域车辆隐私需求的程度.使用深圳市某区的出租车辆的轨迹数据验证了联合熵隐私度量模型及基于该模型的 Mix-zone 创建方案,实验结果表明,该联合熵模型能刻画交通场景中参数与隐私保护程度的正比关系,在联合熵所表示的无序性指标上,所提 Mix-zone 创建方案相较其他方案,具有更好的隐私保护效果.%Aiming at the weak flexibility and lack of users' transparency existing in the current Mix-zone schemes for In-ternet of vehicle (IoV), a dynamic was proposed for Mix-zone construction with traffic adaption, which could construct a Mix-zone for the vehicles dynamically according to the traffic conditions for changing pseudonym at anytime and anywhere. This kind of Mix-zone could achieve privacy-preserving based on the identity and location. In addition, a novel traf-fic-adaptive metric was presented for classifying the privacy leveled in Mix-zone, which applied the normalization quantita-tion to measure the degree of Mix-zone's privacy demanding by the current region. It was verified that the joint entro-py-based privacy measuring model and the Mix-zone construction scheme by utilizing the trajectory data of taxis in certain district in Shenzhen city. The experimental shows that the proposed combination entropy-based model could depict the pro-portional relationship between the traffic scene parameters and the privacy-preserving degrees. The scheme is better in per-formance over the related methods, and strikes a good balance between location privacy and service usability.
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