TY - GEN
T1 - Towards efficient private spatial information retrieval using GPUs
AU - Maruseac, Mihai
AU - Ghinita, Gabriel
AU - Ouyang, Ming
AU - Rughinis, Razvan
N1 - Publisher Copyright:
Copyright 2014 ACM.
PY - 2014/11/4
Y1 - 2014/11/4
N2 - Latest generation mobile devices allow users to receive services tailored to their current locations. Location-based service providers perform spatial queries based on the user locations, but may also share them with various third parties. User whereabouts may disclose sensitive details about an individual's health status, political views or lifestyle choices, and therefore must be thoroughly protected. Private information retrieval (PIR) methods support blind execution of range and NN queries with cryptographic-strength se- curity, but incur significant performance overhead. We employ graphical processing units (GPUs) to speed up the crypto operations required by PIR. We identify the challenges that arise when using GPUs for this purpose, and we propose solutions to ad- dress them. To the best of our knowledge, this is the first work to use GPUs for efficient private spatial information retrieval, and an important first step towards GPU-based acceleration of a broader range of secure spatial data operations.
AB - Latest generation mobile devices allow users to receive services tailored to their current locations. Location-based service providers perform spatial queries based on the user locations, but may also share them with various third parties. User whereabouts may disclose sensitive details about an individual's health status, political views or lifestyle choices, and therefore must be thoroughly protected. Private information retrieval (PIR) methods support blind execution of range and NN queries with cryptographic-strength se- curity, but incur significant performance overhead. We employ graphical processing units (GPUs) to speed up the crypto operations required by PIR. We identify the challenges that arise when using GPUs for this purpose, and we propose solutions to ad- dress them. To the best of our knowledge, this is the first work to use GPUs for efficient private spatial information retrieval, and an important first step towards GPU-based acceleration of a broader range of secure spatial data operations.
KW - GPU
KW - Location Privacy
KW - Private Information Retrieval
UR - http://www.scopus.com/inward/record.url?scp=84961198411&partnerID=8YFLogxK
U2 - 10.1145/2666310.2666431
DO - 10.1145/2666310.2666431
M3 - Conference contribution
AN - SCOPUS:84961198411
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
SP - 405
EP - 408
BT - 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014
A2 - Schneider, Markus
A2 - Gertz, Michael
A2 - Huang, Yan
A2 - Sankaranarayanan, Jagan
A2 - Krumm, John
PB - Association for Computing Machinery
T2 - 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014
Y2 - 4 November 2014 through 7 November 2014
ER -