Cryptology ePrint Archive: Report 2019/1234

Efficient Homomorphic Comparison Methods with Optimal Complexity

Jung Hee Cheon and Dongwoo Kim and Duhyeong Kim

Abstract: Comparison of two numbers is one of the most frequently used operations, but it has been a challenging task to efficiently compute the comparison function in homomorphic encryption (HE) which basically support addition and multiplication. Recently, Cheon et al. (Asiacrypt 2019) introduced a new approximate representation of the comparison function with a rational function, and showed that this rational function can be evaluated by an iterative algorithm. Due to this iterative feature, their method achieves a logarithmic computational complexity compared to previous polynomial approximation methods; however, the computational complexity is still not optimal, and the algorithm is quite slow for large-bit inputs in HE implementation.

In this work, we propose new comparison methods with optimal asymptotic complexity based on composite polynomial approximation. The main idea is to systematically design a constant-degree polynomial $f$ by identifying the core properties to make a composite polynomial $f\circ f \circ \cdots \circ f$ get close to the sign function (equivalent to the comparison function) as the number of compositions increases. Utilizing the devised polynomial $f$, our new comparison algorithms only require $\Theta(\log(1/\epsilon)) + \Theta(\log\alpha)$ computational complexity to obtain an approximate comparison result of $a,b\in[0,1]$ satisfying $|a-b|\ge \epsilon$ within $2^{-\alpha}$ error. The asymptotic optimality results in substantial performance enhancement: our comparison algorithm on encrypted $20$-bit integers for $\alpha = 20$ takes $1.43$ milliseconds in amortized running time, which is $30$ times faster than the previous work.

Category / Keywords: applications / Homomorphic Encryption, Comparison, Min/Max, Composite polynomial approximation

Date: received 21 Oct 2019, last revised 10 Nov 2019

Contact author: jhcheon at snu ac kr,dwkim606@snu ac kr,doodoo1204@snu ac kr

Available format(s): PDF | BibTeX Citation

Version: 20191111:044120 (All versions of this report)

Short URL: ia.cr/2019/1234


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