Privacy-preserving equality test towards big data

Tushar Kanti Saha*, Takeshi Koshiba

*Corresponding author for this work

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

3 Citations (Scopus)


In this paper, we review the problem of private batch equality test (PriBET) that was proposed by Saha and Koshiba (3rd APWConCSE 2016). They described this problem to find the equality of an integer within a set of integers between two parties who do not want to reveal their information if they do not equal. For this purpose, they proposed the PriBET protocol along with a packing method using the binary encoding of data. Their protocol was secured by using ring-LWE based somewhat homomorphic encryption (SwHE) in the semi-honest model. But this protocol is not fast enough to address the big data problem in some practical applications. To solve this problem, we propose a base-N fixed length encoding based PriBET protocol using SwHE in the same semi-honest model. Here we did our experiments for finding the equalities of 8–64-bit integers. Furthermore, our experiments show that our protocol is able to evaluate more than one million (resp. 862 thousand) of equality comparisons per minute for 8-bit (resp. 16-bit) integers with an encoding size of base 256 (resp. 65536). Besides, our protocol works more than 8–20 in magnitude than that of Saha and Koshiba.

Original languageEnglish
Title of host publicationFoundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers
EditorsAbdessamad Imine, Jose M. Fernandez, Luigi Logrippo, Jean-Yves Marion, Joaquin Garcia-Alfaro
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319756493
Publication statusPublished - 2018
Event10th International Symposium on Foundations and Practice of Security, FPS 2017 - Nancy, France
Duration: 2017 Oct 232017 Oct 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10723 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th International Symposium on Foundations and Practice of Security, FPS 2017


  • Base-N encoding
  • Homomorphic encryption
  • Packing method
  • Private batch equality test

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Privacy-preserving equality test towards big data'. Together they form a unique fingerprint.

Cite this