摘要
基于位置服务(LBS)和增强现实技术快速发展的同时,促进了基于位置服务的应用范围扩大,同时也带来了用户位置隐私泄露的隐患,针对这一问题,本文提出一种双重匿名方法保护用户位置隐私,该方法融合自适应k匿名技术和差分隐私技术,根据用户服务请求类型判断隐私等级自适应产生k值,然后通过差分隐私技术随机产生扰动,将扰动位置作为用户真实位置发送给服务提供商.实验结果表明该方法提高了相对匿名度,LBS服务质量也得到保障,从而有效地保护了用户的位置隐私.
Rapid development of location based service(LBS)and augment reality induces to enlargement application of LBS,which also brings hidden danger of disclosure of user location privacy.Here,we suggested a double anonymity privacy method to protect the user location privacy.The adaptive k-anonymity technology and differential privacy technology were combined.k value was generated self-adaptively according to privacy level which was resulted from user service request type.Disturbance location was made through differential privacy technology and sent to service producer as the real user location.Our results indicated that this method can effectively protect the user location privacy with enhanced relative anonymity and LBS service quality.
作者
杨洋
王汝传
Yang Yang;Wang Ruchuan(Institute of Engineering and Information,Nanjing Radio and TV University,Nanjing City Vocational College,Nanjing 210002,China;College of Computer,Nanjing University of Posts and Telecommunications,Nanjing 210003 China;Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing 210003,China)
出处
《南京师大学报（自然科学版）》
CAS
CSCD
北大核心
2018年第3期42-46,共5页
Journal of Nanjing Normal University(Natural Science Edition)
基金
国家自然科学基金(60973139、61170065、61171053)、江苏省自然科学基金(BK2011755)、江苏省科技支撑计划项目(BE2010197、BE2010198、BE2011844、BE2011189).
关键词
基于位置服务
位置隐私
k-匿名法
自适应
差分隐私技术
location based service
location privacy
k-anonymity technology
self-adaption
differential privacy technology
