群智感知网络中轨迹隐私保护方法安全性分析

Security Analysis of Trajectory Privacy Protection Methods in Crowdsensing Networks

摘要: 随着科技与经济的快速发展和移动智能设备层出不穷极大地推动了群智感知(Crowdsensing, CS)网络的发展。其中，轨迹隐私保护方法是群智感知隐私保护研究的热点问题，虽然轨迹隐私保护方法多样，但在具有大规模参与者的群智感知网络中仍存在隐私保护不当的问题。因此，本文对群智感知轨迹隐私保护方法的安全性进行分析，对研究者开展群智感知轨迹隐私保护研究具有重要意义。首先，本文对群智感知轨迹隐私保护面临的安全问题进行详细的阐述。接着归纳总结了现有群智感知轨迹隐私保护方法包括假数据、匿名、抑制和扰动等方法的研究现状和存在的问题。最后，对群智感知轨迹隐私保护方法未来研究方向总结与展望。

Abstract: With the rapid development of technology and economy and the emergence of mobile intelligent devices, the development of crowdsensing networks has been greatly promoted. Among them, trajectory privacy protection methods are a hot topic in the research of crowdsensing privacy protection. Although there are various methods for trajectory privacy protection, there is still a problem of improper privacy protection in crowdsensing networks with large-scale participants. Therefore, this paper analyzes the security of the trajectory privacy protection methods of crowdsensing, which is of great significance for researchers to conduct research on the trajectory privacy protection of crowdsensing. Firstly, this article provides a detailed explanation of the security issues faced by the privacy protection of crowdsensing trajectories. Then, the research status and existing problems of existing crowdsensing trajectory privacy protection methods, including false data, anonymity, suppression, and perturbation methods, were summarized and summarized. Finally, a summary and outlook on the future research directions of crowdsensing trajectory privacy protection methods.