Private Set Intersection for Unequal Set Sizes with Mobile Applications
Private set intersection (PSI) is a cryptographic technique that is applicable to many privacy-sensitive scenarios. For decades, researchers have been focusing on improving its efficiency in both communication and computation. However, most of the existing solutions are inefficient for an unequal nu...
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Online Access: | https://doi.org/10.1515/popets-2017-0044 |
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doaj-c7cded67ab16428d9f177be0756271c72021-09-05T13:59:52ZengSciendoProceedings on Privacy Enhancing Technologies2299-09842017-10-012017417719710.1515/popets-2017-0044popets-2017-0044Private Set Intersection for Unequal Set Sizes with Mobile ApplicationsKiss Ágnes0Liu Jian1Schneider Thomas2Asokan N.3Pinkas Benny4TU DarmstadtAalto UniversityTU DarmstadtAalto University and University of HelsinkiBar Ilan UniversityPrivate set intersection (PSI) is a cryptographic technique that is applicable to many privacy-sensitive scenarios. For decades, researchers have been focusing on improving its efficiency in both communication and computation. However, most of the existing solutions are inefficient for an unequal number of inputs, which is common in conventional client-server settings. In this paper, we analyze and optimize the efficiency of existing PSI protocols to support precomputation so that they can efficiently deal with such input sets. We transform four existing PSI protocols into the precomputation form such that in the setup phase the communication is linear only in the size of the larger input set, while in the online phase the communication is linear in the size of the smaller input set. We implement all four protocols and run experiments between two PCs and between a PC and a smartphone and give a systematic comparison of their performance. Our experiments show that a protocol based on securely evaluating a garbled AES circuit achieves the fastest setup time by several orders of magnitudes, and the fastest online time in the PC setting where AES-NI acceleration is available. In the mobile setting, the fastest online time is achieved by a protocol based on the Diffie-Hellman assumption.https://doi.org/10.1515/popets-2017-0044private set intersectionbloom filteroblivious pseudorandom function |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kiss Ágnes Liu Jian Schneider Thomas Asokan N. Pinkas Benny |
spellingShingle |
Kiss Ágnes Liu Jian Schneider Thomas Asokan N. Pinkas Benny Private Set Intersection for Unequal Set Sizes with Mobile Applications Proceedings on Privacy Enhancing Technologies private set intersection bloom filter oblivious pseudorandom function |
author_facet |
Kiss Ágnes Liu Jian Schneider Thomas Asokan N. Pinkas Benny |
author_sort |
Kiss Ágnes |
title |
Private Set Intersection for Unequal Set Sizes with Mobile Applications |
title_short |
Private Set Intersection for Unequal Set Sizes with Mobile Applications |
title_full |
Private Set Intersection for Unequal Set Sizes with Mobile Applications |
title_fullStr |
Private Set Intersection for Unequal Set Sizes with Mobile Applications |
title_full_unstemmed |
Private Set Intersection for Unequal Set Sizes with Mobile Applications |
title_sort |
private set intersection for unequal set sizes with mobile applications |
publisher |
Sciendo |
series |
Proceedings on Privacy Enhancing Technologies |
issn |
2299-0984 |
publishDate |
2017-10-01 |
description |
Private set intersection (PSI) is a cryptographic technique that is applicable to many privacy-sensitive scenarios. For decades, researchers have been focusing on improving its efficiency in both communication and computation. However, most of the existing solutions are inefficient for an unequal number of inputs, which is common in conventional client-server settings. In this paper, we analyze and optimize the efficiency of existing PSI protocols to support precomputation so that they can efficiently deal with such input sets. We transform four existing PSI protocols into the precomputation form such that in the setup phase the communication is linear only in the size of the larger input set, while in the online phase the communication is linear in the size of the smaller input set. We implement all four protocols and run experiments between two PCs and between a PC and a smartphone and give a systematic comparison of their performance. Our experiments show that a protocol based on securely evaluating a garbled AES circuit achieves the fastest setup time by several orders of magnitudes, and the fastest online time in the PC setting where AES-NI acceleration is available. In the mobile setting, the fastest online time is achieved by a protocol based on the Diffie-Hellman assumption. |
topic |
private set intersection bloom filter oblivious pseudorandom function |
url |
https://doi.org/10.1515/popets-2017-0044 |
work_keys_str_mv |
AT kissagnes privatesetintersectionforunequalsetsizeswithmobileapplications AT liujian privatesetintersectionforunequalsetsizeswithmobileapplications AT schneiderthomas privatesetintersectionforunequalsetsizeswithmobileapplications AT asokann privatesetintersectionforunequalsetsizeswithmobileapplications AT pinkasbenny privatesetintersectionforunequalsetsizeswithmobileapplications |
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1717812853786804224 |