计算机科学
空间查询
空间分析
数据挖掘
信息隐私
明文
领域(数学)
范围查询(数据库)
空间数据库
外包
光学(聚焦)
云计算
查询优化
情报检索
Web搜索查询
Web查询分类
加密
计算机安全
地理
搜索引擎
遥感
物理
数学
光学
政治学
纯数学
法学
操作系统
作者
Yinbin Miao,Yutao Yang,Xinghua Li,Kim‐Kwang Raymond Choo,Xiangdong Meng,Robert H. Deng
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2023-07-25
卷期号:24 (12): 13603-13616
被引量:5
标识
DOI:10.1109/tits.2023.3295798
摘要
With the rapid development of Intelligent Transportation System (ITS), a large number of spatial data are generated in ITS. Although outsourcing spatial data to the cloud server can reduce the high local computation and storage overheads, it will also lead to security and privacy issues. Therefore, it is necessary to have a survey to specifically summarize these advanced privacy-preserving spatial data query schemes. However, the existing surveys considering both location information and keywords of spatial data only summarize the spatial keyword query scheme in plaintext environment, they do not consider the privacy of spatial data. Although there are some surveys on privacy-preserving spatial data query, they only focus on the location information of spatial data without considering descriptive keywords. Therefore, to understand the progress and research trends in the field, we give a comprehensive survey on secure spatial data query in ITS to summarize and analyze the most advanced solutions. Then, we make a comprehensive and detailed comparison of existing solutions in terms of query function, index structure, time complexity, security, etc. Finally, we show some open challenges and potential research directions for privacy-preserving spatial data query.
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