基于时空关联的车联网假位置筛选算法
A dummy location screening algorithm based on spatial-temporal correlation in Internet of Vehicles
张琳 1于子豪 2刘茜萍1
作者信息
- 1. 南京邮电大学 计算机学院,江苏 南京 210023;江苏省无线传感网高技术研究重点实验室,江苏 南京 210003
- 2. 南京邮电大学 计算机学院,江苏 南京 210023
- 折叠
摘要
目前,车联网位置隐私保护方法没有充分考虑到不同的时间段内假位置查询概率的变化,同时忽视了对于连续时间背景下同一位置单元每天的用户访问量变化趋势有较大差异的问题.针对上述缺陷,提出空间敏感度度量标准,在选择假位置时综合考虑位置语义相似度提出语义-空间敏感度期望的筛选指标,生成满足分时间段查询概率、匿名区域面积要求的假位置集合.实验结果证明了新算法的可行性及有效性,能够适应当下的车联网位置隐私保护需求.
Abstract
At present,the location privacy protection methods of Internet of Vehicles do not fully consider the change of fake location query probability in different time periods,and ignore the problem that the amount of daily users access to the same location unit varies largely during a continuous time.Therefore,a spatial sensitivity measurement algorithm is proposed in this paper.This algorithm considers the location semantic similarity when selecting the fake location.And a screening index of semantic-spatial sensitivity expectation is provided and a fake location set that meets the requirements of query probability in different time segments and anonymous area is generated.Experimental results demonstrate the feasibility and effectiveness of the proposed algorithm.It can fit the current requirements of location privacy protection for the Internet of vehicles.
关键词
车联网/基于位置的服务/空间敏感度/语义相似度/位置隐私/时空关联性Key words
Internet of Vehicles(IoV)/location based services(LBS)/spatial sensitivity/semantic similarity/location privacy/spatio-temporal correlation引用本文复制引用
基金项目
国家自然科学基金(61572260)
国家自然科学基金(61872196)
国家自然科学基金(61872194)
江苏省科技支撑计划(BE2017166)
南京邮电大学校级自然科学基金(NY222142)
出版年
2024
国家科技期刊平台
NSTL
万方数据