Abstract
Location-based services offer immense utility, but also pose significant privacy risks. In response, we propose LocPIR, a novel framework using homomorphic encryption (HE), specifically the TFHE scheme, to preserve user location privacy when retrieving data from public clouds. Our system employs TFHE's expertise in non-polynomial evaluations, crucial for comparison operations. LocPIR showcases minimal client-server interaction, reduced memory overhead, and efficient throughput. Performance tests confirm its computational speed, making it a viable solution for practical scenarios, demonstrated via application to a COVID-19 alert model. Thus, LocPIR effectively addresses privacy concerns in location-based services, enabling secure data sharing from the public cloud.
Original language | English |
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Title of host publication | AVSS 2024 - 20th IEEE International Conference on Advanced Video and Signal-Based Surveillance |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Edition | 2024 |
ISBN (Electronic) | 9798350374285 |
DOIs | |
Publication status | Published - 2024 |
Event | 20th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2024 - Niagara Falls, Canada Duration: 2024 Jul 15 → 2024 Jul 16 |
Conference
Conference | 20th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2024 |
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Country/Territory | Canada |
City | Niagara Falls |
Period | 24/7/15 → 24/7/16 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Signal Processing
- Media Technology