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Efficient and Secure Algorithms for GLV-Based Scalar Multiplication and Their Implementation on GLV-GLS Curves

机译:基于GLV的标量乘法的高效安全算法及其在GLV-GLS曲线上的实现

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We propose efficient algorithms and formulas that improve the performance of side-channel protected scalar multiplication exploiting the Gallant-Lambert-Vanstone (CRYPTO 2001) and Galbraith-Lin-Scott (EUROCRYPT 2009) methods. Firstly, by adapting Feng et al.'s recoding to the GLV setting, we derive new regular algorithms for variable-base scalar multiplication that offer protection against simple side-channel and timing attacks. Secondly, we propose an efficient technique that interleaves ARM-based and NEON-based multiprecision operations over an extension field, as typically found on GLS curves and pairing computations, to improve performance on modern ARM processors. Finally, we showcase the efficiency of the proposed techniques by implementing a state-of-the-art GLV-GLS curve in twisted Edwards form defined over F_(p~2), which supports a four dimensional decomposition of the scalar and runs in constant time, i.e., it is fully protected against timing attacks. For instance, using a precomputed table of only 512 bytes, we compute a variable-base scalar multiplication in 92,000 cycles on an Intel Ivy Bridge processor and in 244,000 cycles on an ARM Cortex-A15 processor. Our benchmark results and the proposed techniques contribute to the improvement of the state-of-the-art performance of elliptic curve computations. Most notably, our techniques allow us to reduce the cost of adding protection against timing attacks in the GLV-based variable-base scalar multiplication computation to below 10%.
机译:我们提出有效的算法和公式,以利用Gallant-Lambert-Vanstone(CRYPTO 2001)和Galbraith-Lin-Scott(EUROCRYPT 2009)方法来改善侧信道保护标量乘法的性能。首先,通过使Feng等人的编码适应GLV设置,我们得出了用于可变基标量乘法的新常规算法,该算法可提供针对简单边信道和定时攻击的保护。其次,我们提出了一种有效的技术,该技术可以在扩展字段上交织基于ARM和基于NEON的多精度操作(通常在GLS曲线和配对计算中找到),以提高现代ARM处理器的性能。最后,我们通过在F_(p〜2)上定义的扭曲Edwards形式实现最新的GLV-GLS曲线,展示了所提出技术的效率,该曲线支持标量的四维分解并以常数运行时间,即完全保护它免受定时攻击。例如,使用仅512字节的预先计算表,我们在Intel Ivy Bridge处理器上以92,000个周期和在ARM Cortex-A15处理器上以244,000个周期计算了基于变量的标量乘法。我们的基准测试结果和提出的技术有助于改善椭圆曲线计算的最新性能。最值得注意的是,我们的技术使我们能够将基于GLV的基于变量的标量乘法计算中的针对定时攻击的保护成本降低至10%以下。

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