计算机科学
加密
密码学
索引(排版)
情报检索
嵌入
理论计算机科学
数据挖掘
数据库
万维网
算法
人工智能
计算机安全
作者
Zhen Lv,Ke Shang,Hongwei Huo,Ximeng Liu,Yanguo Peng,Xiangyu Wang,Yan Tan
出处
期刊:IEEE Transactions on Services Computing
[Institute of Electrical and Electronics Engineers]
日期:2023-09-01
卷期号:16 (5): 3621-3635
标识
DOI:10.1109/tsc.2023.3289654
摘要
Spatial keyword queries have attracted much attention over the past decade due to the popularity of location-based services and social networks, which brings great economic benefits. Geo-textual data are encrypted-and-delegated to public clouds for efficient management and utilization while preventing potential data leakage. However, it is still challenging to solve secure ra nge s patial k eyword queries on encrypted data since existing works are either vulnerable or inefficient. In this paper, a secure hybrid index is built to implement efficient filtering, by embedding nodes' paths in a novel symmetrical kd-tree into inverted indexes and employing only lightweight cryptographic techniques. A concrete scheme RASK is constructed on the secure index by utilizing only a little storage and computing resources of clients. Furthermore, RASK+ is proposed based on secure virtual technology by migrating all storage burdens from clients to public clouds. Both schemes are theoretically proved to be indistinguishable under adaptive chosen keyword attacks (IND-CKA2). Through experimental evaluations on three real datasets within consistent environments, both schemes reduce the response time by about 50%-80% compared to state-of-the-art solutions (i.e., SKSE, LSKQ, etc.). The storage overheads for the cloud are also reduced by about 0.5-2 orders of magnitude.
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