首页 | 本学科首页   官方微博 | 高级检索  
     

个性化时空数据隐私保护
引用本文:刘向宇,夏国平,夏秀峰,宗传玉,朱睿,李佳佳. 个性化时空数据隐私保护[J]. 计算机应用, 2021, 41(3): 643-650. DOI: 10.11772/j.issn.1001-9081.2020091463
作者姓名:刘向宇  夏国平  夏秀峰  宗传玉  朱睿  李佳佳
作者单位:沈阳航空航天大学 计算机学院, 沈阳 110136
基金项目:国家自然科学基金资助项目;辽宁省自然科学基金计划重点项目
摘    要:智能移动终端的普及导致收集的时空数据中个人位置隐私、签到数据隐私、轨迹隐私等敏感信息容易泄露,且当前研究分别针对上述隐私泄露单独提出保护技术,而没有面向用户给出防止上述隐私泄露的个性化时空数据隐私保护方法.针对这个问题,提出一种面向时空数据的个性化隐私保护模型(p,q,ε)-匿名和基于该模型的个性化时空数据隐私保护(P...

关 键 词:时空数据  隐私保护  个性化  数据可用性  泛化匿名
收稿时间:2020-09-07
修稿时间:2020-10-17

Personalized privacy protection for spatio-temporal data
LIU Xiangyu,XIA Guoping,XIA Xiufeng,ZONG Chuanyu,ZHU Rui,LI Jiajia. Personalized privacy protection for spatio-temporal data[J]. Journal of Computer Applications, 2021, 41(3): 643-650. DOI: 10.11772/j.issn.1001-9081.2020091463
Authors:LIU Xiangyu  XIA Guoping  XIA Xiufeng  ZONG Chuanyu  ZHU Rui  LI Jiajia
Affiliation:College of Computer Science, Shenyang Aerospace University, Shenyang Liaoning 110136, China
Abstract:Due to the popularity of smart mobile terminals, sensitive information such as personal location privacy, check-in data privacy and trajectory privacy in the collected spatio-temporal data are easy to be leaked. In the current researches, protection technologies are proposed for the above privacy leakages respectively, and there is not a personalized spatio-temporal data privacy protection method to prevent the above privacy leakages for users. Therefore, a personalized privacy protection model for spatio-temporal data named (p,q,ε)-anonymity and a Personalized Privacy Protection for Spatio-Temporal Data (PPPST) algorithm based on this model were proposed to protect the users' privacy data with personalized settings (location privacy, check-in data privacy and trajectory privacy). The heuristic rules were designed to generalize the spatio-temporal data to ensure the availability of the published data and realize the high availability of spatio-temporal data. In the comparison experiments, the data availability rate of PPPST algorithm is about 4.66% and 15.45% higher than those of Information Data Used through K-anonymity (IDU-K) and Personalized Clique Cloak (PCC) algorithms on average respectively. At the same time, the generalized location search technology was designed to improve the execution efficiency of the algorithm. Experiments and analysis were conducted based on real spatio-temporal data. Experimental results show that PPPST algorithm can effectively protect the privacy of personalized spatio-temporal data.
Keywords:spatio-temporal data  privacy protection  personalized  data utility  generalized anonymity  
本文献已被 万方数据 等数据库收录!
点击此处可从《计算机应用》浏览原始摘要信息
点击此处可从《计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号