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New and Improved Methods to Analyze and Compute Double-Scalar Multiplications

机译:分析和计算双标量乘法的新方法和改进方法

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We address several algorithms to perform a double-scalar multiplication on an elliptic curve. All the methods investigated are related to the double-base number system (DBNS) and extend previous work of Doche et al. . We refine and rigorously prove the complexity analysis of the joint binary-ternary (JBT) algorithm. Experiments are in line with the theory and show that the JBT requires approximately 6 percent less field multiplications than the standard joint sparse form (JSF) method to compute $([{schmi{n}}]{schmi{P}} + [{schmi{m}}]{schmi{Q}})$. We also introduce a randomized version of the JBT, called JBT-Rand, that gives total control of the number of triplings in the expansion that is produced. So it becomes possible with the JBT-Rand to adapt and tune the number of triplings to the coordinate system and bit length that are used, to further decrease the cost of a double-scalar multiplication. Then, we focus on Koblitz curves. For extension degrees enjoying an optimal normal basis of type II, we discuss a Joint $({schmi{tau}})$-DBNS approach that reduces the number of field multiplications by at least 35 percent over the traditional $({schmi{tau}})$-JSF. For other extension degrees represented in polynomial basis, the Joint $({schmi{tau}})$-DBNS is still relevant provided that appropriate bases conversion methods are used. In this situation, tests show that the speedup over the $({schmi{tau}})$-JSF is then larger than 20 percent. Finally, when the use of the $({schmi{tau}})$-DBNS becomes unrealistic, for instance because of the lack of an efficient normal basis or the lack of memory to allow an efficient conversion, we adapt the joint binary-ternary algorithm to Koblitz curves giving rise to the Joint $({schmi{tau}})$-$(bar{{schmi{tau}} })$ method whose complexity is analyzed and proved. The Joint $({schmi{tau}})$-$(bar{{schmi{tau}} })$ induces a speedup of about 10 percent over the $({schmi{tau}})$-JSF.
机译:我们讨论了几种在椭圆曲线上执行双标量乘法的算法。所有研究的方法都与双基数系统(DBNS)有关,并扩展了Doche等人以前的工作。 。我们改进并严格证明了联合二进制三进制(JBT)算法的复杂度分析。实验符合该理论,并显示与标准联合稀疏形式(JSF)方法相比,JBT计算$([{{schmi {n}}] {schmi {P}} + [{ schmi {m}}] {schmi {Q}})$。我们还引入了JBT的随机版本,称为JBT-Rand,它可以完全控制所产生的扩展中的三倍数量。因此,使用JBT-Rand可以对所使用的坐标系和位长进行三倍调整和调整,以进一步降低双标量乘法的成本。然后,我们关注Koblitz曲线。对于享有II类最佳正态基础的扩展程度,我们讨论了一种联合$({schmi {tau}})$-DBNS方法,该方法可将字段乘法次数比传统的$({schmi {tau }})$-JSF。对于使用多项式表示的其他扩展度,如果使用适当的基数转换方法,则联合$({schmi {tau}})$-DBNS仍然适用。在这种情况下,测试表明,$({schmi {tau}})$-JSF的提速比大于20%。最后,当使用$({schmi {tau}})$-DBNS变得不切实际时,例如,由于缺乏有效的正常基础或内存不足以进行有效的转换,我们采用联合二进制- Koblitz曲线的三元算法产生了联合$({schmi {tau}})$-$(bar {{schmi {tau}}}})$方法,并对其复杂性进行了分析和证明。联合$({schmi {tau}})$-$(bar {{schmi {tau}}}} $的速度比$({schmi {tau}})$-JSF快约10%。

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