Personalized Location Privacy Protection Based on Vehicle Movement Regularity in Vehicular Networks
Personalized Location Privacy Protection Based on Vehicle Movement Regularity in Vehicular Networks
复制标题
车载网络中基于车辆运动规律的个性化位置隐私保护
DOI：
10.1109/jsyst.2020.3047397
复制
发表时间：
2021-01
影响因子：
4.4
通讯作者：
Lu Liu
中科院分区：
文献类型：
--
作者：
Hong Zhong;Jingyue Ni;Jie Cui;Jing Zhang;Lu Liu
目前，位置隐私问题越来越受到关注。在传统的基于假名的解决方案中，每个车辆的假名年龄以相同的速率增加，并且车辆在遇到车辆时改变其假名，车辆也希望在相同的位置改变假名。但是，我们观察到，根据每辆车车主的个人特点，每辆车的运动是有规律的，即，有些地方是车辆经常去的，有些地方是车辆很少去的。显然，这些地方的假名改变策略是不同的。为了解决这些问题，我们提出了一个基于敏感性的假名变化机制，它可以充分利用车辆的运动规律，从而实现个性化的位置隐私。假名年龄分析模型被用来量化所实现的位置隐私。此外，我们提出了一个新的度量标准来衡量个性化的位置隐私保护的水平。性能评估的结果表明，我们的方法显着优于现有的方法在实现个性化的位置隐私。
Currently, the issue of location privacy has been attracting increasing attention. In traditional pseudonym-based solutions, the pseudonym age of each vehicle increases at the same rate and vehicles change their pseudonyms when they meet vehicles, which also want to change pseudonyms at the same location. However, we observe that according to the individual characteristics of each vehicle’s owner, the movement of each vehicle is regular, i.e., there are some locations that vehicles visit frequently, and some locations that they rarely visit. Evidently, pseudonym change strategies for these locations are different. To address these issues, we propose a sensitivity-based pseudonym change mechanism, which can take full advantage of the regularity of a vehicle’s movement, thereby achieving personalized location privacy. A pseudonym age analytical model is used to quantify the achieved location privacy. Furthermore, we propose a new metric to measure the level of personalized location privacy protection. The results of the performance evaluation demonstrate that our approach significantly outperforms existing approaches in realizing personalized location privacy.