首页> 外文会议>International Workshop on Security(IWSEC 2007); 20071029-31; Nara(JP) >Reduction Optimal Trinomials for Efficient Software Implementation of the η_T Pairing
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Reduction Optimal Trinomials for Efficient Software Implementation of the η_T Pairing

机译:简化的最佳三项式用于η_T配对的高效软件实现

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The η_T pairing for supersingular elliptic curve over GF(3~m) has been paid attention because of its computational efficiency. Since most parts of computation of the η_T pairing are multiplications over GF(3~m), it is important to improve the speed of the multiplication when implementing the η_T pairing. In this paper we consider software implementation of multiplication over GF(3~m) and propose to use irreducible trinomials x~m + ax~k + b over GF(3) such that w, bit length of word of targeted CPU, divides k. We call the trinomials "reduction optimal trinomials (ROTs)". ROTs actually exist for several m's and typical values of w = 16 and 32. We list them for extension degrees m = 97, 167, 193 and 239. These m's are derived from security considerations. Using ROT it is possible to implement efficient modulo operation (reduction) in multiplication over GF(3~m) comparing with the case using other type of trinomials (e.g., trinomials with minimum k for each m). The reason of this is that for the cases of reduction by ROT the number of shift operations on multiple precision data reduces to less than half comparing with the cases by other trinomials. Implementation results show that reduction algorithm specialized for ROT is 20-30% faster on 32-bit CPU and around 40% faster on 16-bit CPU than algorithm for irreducible trinomials with general k.
机译:GF(3〜m)上奇异椭圆曲线的η_T配对由于其计算效率而受到关注。由于η_T配对的大部分计算都是在GF(3〜m)上进行乘法运算,因此实现η_T配对时提高乘法速度非常重要。在本文中,我们考虑了在GF(3〜m)上进行乘法的软件实现,并建议在GF(3)上使用不可约的三项式x〜m + ax〜k + b,以便w,目标CPU的字的位长除以k 。我们称这些三项式为“归约最优三项式(ROT)”。 ROT实际上存在几个m,典型值w = 16和32。我们列出了它们的扩展度m = 97、167、193和239。这些m是出于安全考虑。与使用其他类型的三项式(例如,每m最小k的三项式)的情况相比,使用ROT可以在GF(3〜m)上实现有效的模运算(归约)。这是因为,对于通过ROT减少的情况,与其他三项式的情况相比,对多个精度数据进行移位运算的次数减少到少于一半。实施结果表明,专用于ROT的约简算法在32位CPU上比在通用k下不可约三项式的算法快20-30%,在16位CPU上快40%。

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