Cryptology ePrint Archive: Report 2020/181

$L_1$-Norm Ball for CSIDH: Optimal Strategy for Choosing the Secret Key Space

Kohei Nakagawa and Hiroshi Onuki and Atsushi Takayasu and Tsuyoshi Takagi

Abstract: Isogeny-based cryptography is a kind of post-quantum cryptography whose security relies on the hardness of an isogeny problem over elliptic curves. In this paper, we study CSIDH, which is one of isogeny-based cryptography presented by Castryck et al. in Asiacrypt 2018. In CSIDH, the secret key is taken from an $L_\infty$-norm ball of integer vectors and the public key is generated by calculating the action of an ideal class corresponding to a secret key. For faster key exchange, it is important to accelerate the algorithm calculating the action of the ideal class group, many such approaches have been studied recently. Several papers showed that CSIDH becomes more efficient when a secret key space is changed to weighted $L_\infty$-norm ball. In this paper, we revisit the approach and try to find an optimal secret key space which minimizes the computational cost of the group action. At first, we obtain an optimal secret key space by analyzing computational cost of CSIDH with respect to the number of operations on $\mathbb{F}_p$. Since the optimal key space is too complicated to sample a secret key uniformly, we approximate the optimal key space by using $L_1$-norm ball and propose algorithms for uniform sampling with some precomputed table. By experiment with CSIDH-512, we show that the computational cost of the $L_1$-norm ball is reduced by about 20\% compared to that of the $L_\infty$-norm ball, using a precomputed table of 160 Kbytes. The cost is only 1.08 times of the cost of the optimal secret key space. Finally, we also discuss possible sampling algorithms using other norm balls and their efficiency.

Category / Keywords: public-key cryptography / post-quantum cryptography, CSIDH, supersingular elliptic curve

Date: received 14 Feb 2020

Contact author: kouhei_nakagawa at mist i u-tokyo ac jp

Available format(s): PDF | BibTeX Citation

Version: 20200214:082515 (All versions of this report)

Short URL: ia.cr/2020/181


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