Fast Private Location-based Information Retrieval over the Torus

Joon Soo Yoo, Mi Yeon Hong, Ji Won Heo, Kang Hoon Lee, Ji Won Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationAVSS 2024 - 20th IEEE International Conference on Advanced Video and Signal-Based Surveillance
PublisherInstitute of Electrical and Electronics Engineers Inc.
Edition2024
ISBN (Electronic)9798350374285
DOIs
Publication statusPublished - 2024
Event20th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2024 - Niagara Falls, Canada
Duration: 2024 Jul 152024 Jul 16

Conference

Conference20th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2024
Country/TerritoryCanada
CityNiagara Falls
Period24/7/1524/7/16

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Media Technology

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