International Association
for Cryptologic Research

Let $E_a/ \mathbb{F}_{2}: y^2+xy=x^3+ax^2+1$ be a Koblitz curve. The window $\tau$-adic non-adjacent form (window $\tau$NAF) is currently the standard representation system to perform scalar multiplications on $E_a/ \mathbb{F}_{2^m}$ utilizing the Frobenius map $\tau$. This work focuses on the pre-computation part of scalar multiplication. We first introduce $\mu\bar{\tau}$-operations where $\mu=(-1)^{1-a}$ and $\bar{\tau}$ is the complex conjugate of $\tau$. Efficient formulas of $\mu\bar{\tau}$-operations are then derived and used in a novel pre-computation scheme. Our pre-computation scheme requires $6${\bf M}$+6${\bf S}, $18${\bf M}$+17${\bf S}, $44${\bf M}$+32${\bf S}, and $88${\bf M}$+62${\bf S} ($a=0$) and $6${\bf M}$+6${\bf S}, $19${\bf M}$+17${\bf S}, $46${\bf M}$+32${\bf S}, and $90${\bf M}$+62${\bf S} ($a=1$) for window $\tau$NAF with widths from $4$ to $7$ respectively. It is about two times faster, compared to the state-of-the-art technique of pre-computation in the literature. The impact of our new efficient pre-computation is also reflected by the significant improvement of scalar multiplication. Traditionally, window $\tau$NAF with width at most $6$ is used to achieve the best scalar multiplication. Because of the dramatic cost reduction of the proposed pre-computation, we are able to increase the width for window $\tau$NAF to $7$ for a better scalar multiplication. This indicates that the pre-computation part becomes more important in performing scalar multiplication. With our efficient pre-computation and the new window width, our scalar multiplication runs in at least 85.2\% the time of Kohel's work (Eurocrypt'2017) combining the best previous pre-computation. Our results push the scalar multiplication of Koblitz curves, a very well-studied and long-standing research area, to a significant new stage.

Double-base chains (DBCs) are widely used to speed up scalar multiplications on elliptic curves. We present three results of DBCs. First, we display a structure of the set containing all DBCs and propose an iterative algorithm to compute the number of DBCs for a positive integer. This is the first polynomial time algorithm to compute the number of DBCs for positive integers. Secondly, we present an asymptotic lower bound on average Hamming weights of DBCs $\frac{\log n}{8.25}$ for a positive integer $n$. This result answers an open question about the Hamming weights of DBCs. Thirdly, we propose a new algorithm to generate an optimal DBC for any positive integer. The time complexity of this algorithm is $\mathcal{O}\left(\left(\log n\right)^2 \log\log n\right)$ bit operations and the space complexity is $\mathcal{O}\left(\left(\log n\right)^{2}\right)$ bits of memory. This algorithm accelerates the recoding procedure by more than $6$ times compared to the state-of-the-art Bernstein, Chuengsatiansup, and Lange's work. The Hamming weights of optimal DBCs are over $60$\% smaller than those of NAFs. Experimental results show that scalar multiplication using our optimal DBC is about $13$\% faster than that using non-adjacent form on elliptic curves over large prime fields.