基于HST的空间众包位置隐私保护方法  

LOCATION PRIVACY PROTECTION METHOD OF SPATIAL CROWDSOURCING BASED ON HST

作　　者：唐旭 龙士工[1,2] 刘海 弓晓锋[3] Tang Xu;Long Shigong;Liu Hai;Gong Xiaofeng(College of Computer Science and Technology,Guizhou University,Guiyang 550025,Guizhou,China;State Key Laboratory of Public Big Data,Guizhou University,Guiyang 550025,Guizhou,China;Guizhou Science and Technology Information Center,Guiyang 550025,Guizhou,China)

机构地区：[1]贵州大学计算机科学与技术学院,贵州贵阳550025 [2]贵州大学公共大数据国家重点实验室,贵州贵阳550025 [3]贵州省科技信息中心,贵州贵阳550025

出　　处：《计算机应用与软件》2025年第1期287-293,共7页Computer Applications and Software

基　　金：国家自然科学基金项目(62062020,62002081);贵州省科技计划基金项目(黔科合重大专项字[2018]3001,黔科合基础[2019]1425)。

摘　　要：针对空间众包中不可信的服务器获取用户真实的位置信息,导致用户隐私泄露的问题。提出一种基于层次分离树(HST)的空间众包位置隐私保护方法,用于保护用户的位置隐私和保证任务分配的有效性,将位置点集构造一个HST,设计一种基于HST的差分隐私保护机制,对用户的位置节点进行扰动处理,并且理论证明该机制满足地理不可区分性。实验结果表明,在相同的隐私预算下,该方法在任务分配的总距离方面明显优于现有的差分隐私机制。Aiming at the problem that the untrusted server in spatial crowdsourcing obtains the user's real location information,resulting in the disclosure of user privacy,we propose a location privacy protection method of space crowdsourcing based on hierarchically well-separated tree(HST),which can protect the user's location privacy and guarantee the effectiveness of the task assignment.It constructed the set of position points into an HST and designed a differential privacy protection mechanism based on HST to conduct disturbance processing on the user's location node.The theory shows that the mechanism meets the Geo-indistinguishability.Experimental results show that under the same privacy budget,the proposed method is significantly better than the existing differential privacy mechanism in the total distance of task assignment.

关 键 词：空间众包 位置隐私 地理不可区分性 任务分配 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]