Welcome to the resource topic for 2022/338
Title:
Private Intersection-Weighted-Sum
Authors: Koji Chida, Koki Hamada, Atsunori Ichikawa, Masanobu Kii, Junichi Tomida
Abstract:We propose secure two-party computation for a new functionality that we call Private Intersection-Weighted-Sum (PIW-Sum) and present an efficient semi-honestly secure protocol. In this computation, two parties own integer matrices \mathbf{X} and \mathbf{Y}, respectively, where each row of the matrices is associated with an identifier. Let I=(i_{1} ,..., i_{n}) be the intersection of the identifier sets for the two parties. The goal is to compute the matrix \widehat{\mathbf{Y}}^{\top}\widehat{\mathbf{X}} together with the cardinality |I|, where the j-th rows of \widehat{\mathbf{X}} and \widehat{\mathbf{Y}} are the rows of \mathbf{X} and \mathbf{Y} with identifier i_{j}, respectively. This functionality is a generalization of Private Intersection-Sum (PI-Sum) proposed by Ion et al.~(EuroS&P’20) and has important real-world applications such as computing a cross tabulation after the equijoin of two tables owned by different parties. Our protocol is built on a new variant of oblivious pseudorandom function (OPRF), and we construct the new variant of OPRF from the decisional Diffie-Hellman (DDH) assumption. We implement both our PIW-Sum protocol and the the most efficient PI-Sum protocol by Ion et al.~and compare their performance in the same environment. This shows that both communication cost and computational cost of our protocol are only about 2 times greater than those of the PI-Sum protocol in the case where \mathbf{X} and \mathbf{Y} are column vectors, i.e., the number of columns of \mathbf{X} and \mathbf{Y} is one.
ePrint: https://eprint.iacr.org/2022/338
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