Abstract
Location-Based Services (LBSs) depend on a Service Provider (SP) to store data owners’ geospatial data and to process data users’ queries. For example, a Yelp user queries the SP to retrieve the k nearest Starbucks by submitting her/his current location. It is well-acknowledged that location privacy is vital to users and several prominent Secure k Nearest Neighbor (SkNN) query processing schemes are proposed. We observe that no prior work addresses the requirement of repetitive query after index update and its privacy issue, i.e., how to match a data item from the cloud repetitively in an oblivious and unlinkable manner. Meanwhile, a malicious SP may skip some data items and recommend others due to unfair competition. In this work, we formally define the repetitive query and its privacy objectives and present an Repetitive, Oblivious, and Unlinkable SkNN scheme ROU. Specifically, we design a multi-level structure to organize locations to further improve search efficiency. Second, we integrate data item identity into the framework of existing SkNN query processing. Data owners encrypt their data item identity and location information into a secure index, and data users encrypt a customized identity range of a previously retrieved data item and location information into a token. Next, the SP uses the token to query the secure index to find the specific data item via privacy-preserving range querying. We formally prove the privacy of ROU in the random oracle model. We build a prototype based on a server to evaluate the performance with a real-world dataset. Experimental results show that ROU is efficient and practical in terms of computational cost, communication overhead, and result verification.
Original language | English |
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Title of host publication | Information and Communications Security - 24th International Conference, ICICS 2022, Proceedings |
Editors | Cristina Alcaraz, Liqun Chen, Shujun Li, Pierangela Samarati |
Place of Publication | Germany |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 261-280 |
Number of pages | 20 |
Edition | 1 |
ISBN (Electronic) | 9783031157776 |
ISBN (Print) | 9783031157769 |
DOIs | |
Publication status | Published - 2022 |
Event | 24th International Conference on Information and Communications Security, ICICS 2022 - Canterbury, United Kingdom Duration: 5 Sept 2022 → 8 Sept 2022 Conference number: 24 https://icics2022.cyber.kent.ac.uk/ |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13407 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 24th International Conference on Information and Communications Security, ICICS 2022 |
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Abbreviated title | ICICS 2022 |
Country/Territory | United Kingdom |
City | Canterbury |
Period | 5/09/22 → 8/09/22 |
Internet address |