三维空间位置服务中智能语义位置隐私保护方法  

Intelligent Semantic Location Privacy Protection Method for Location Based Services in Three-Dimensional Spaces

作　　者：闵明慧 杨爽 胥俊怀 李鑫 李世银 肖亮[3] 彭国军[2] MIN Minghui;YANG Shuang;XU Junhuai;LI Xin;LI Shiyin;XIAO Liang;PENG Guojun(School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China;Key Laboratory of Aerospace Information Security and Trusted Computing,Ministry of Education,Wuhan University,Wuhan 430072,China;School of Informatics,Xiamen University,Xiamen 361005,China)

机构地区：[1]中国矿业大学信息与控制工程学院,徐州221116 [2]武汉大学空天信息安全与可信计算教育部重点实验室,武汉430072 [3]厦门大学信息学院,厦门361005

出　　处：《电子与信息学报》2024年第6期2627-2637,共11页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(62101557,62371451,U21A20444);徐州市基础研究计划项目-青年科技人才项目(KC23022);中国博士后科学基金(2022M713378);中央高校基本科研业务费专项资金(2042022kf0021)。

摘　　要：针对大型医院、商场及其他3维(3D)空间位置服务中敏感语义位置(如药店、书店等)隐私泄露问题,该文研究了基于3D空间地理不可区分性(3D-GI)的智能语义位置隐私保护方法。为摆脱对特定环境和攻击模型的依赖,该文利用强化学习(RL)技术实现对用户语义位置隐私保护策略的动态优化,提出基于策略爬山算法(PHC)的3D语义位置扰动机制。该机制通过诱导攻击者推断较低敏感度的语义位置来减少高敏感语义位置的暴露。为解决复杂3D空间环境下的维度灾难问题,进一步提出基于近端策略优化算法(PPO)的3D语义位置扰动机制,利用神经网络捕获环境特征并采用离线策略梯度方法优化神经网络参数更新,提高语义位置扰动策略选择效率。仿真实验结果表明,所提方法可提升用户的语义位置隐私保护性能和服务体验。An intelligent semantic location privacy protection method based on 3D Geo-Indistinguishability(3DGI)is studied for the privacy leakage problem of sensitive semantic locations(such as medicine stores and bookstores)in 3D space location-based services,such as hospitals and shopping centers.Reinforcement Learning(RL)techniques are used in this paper to optimize user’s semantic location privacy protection policies dynamically.Specifically,a 3D semantic location perturbation mechanism is proposed based on the Policy Hill Climbing(PHC)algorithm,independent of specific environments and attack models.This mechanism induces attackers to infer less sensitive locations to reduce the exposure of sensitive semantic locations.To address the dimensional disaster problem of complex 3D space,a 3D semantic location perturbation mechanism based on the Proximal Policy Optimization(PPO)algorithm is further proposed.This mechanism captures the environment features using a neural network and optimizes the neural network parameter updates through the offline policy gradient method to improve the efficiency of semantic location perturbation policy selection.Experimental results show that the proposed mechanism improves both semantic location privacy protection and user service experience.

关 键 词：位置服务 3维空间 语义位置隐私 策略爬山 近端策略优化 

分 类 号：TN929.5[电子电信—通信与信息系统]