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Improved Composite Order Bilineai Pairing on Graphics Hardware

机译:图形硬件上改进的复合订单Bilineai配对

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摘要

Composite-order bilinear pairing has been applied in many cryptographic constructions, such as identity based encryption, attribute based encryption, and leakage resilient cryptography. However, the computation of such pairing is relatively slow since the composite order should be at least 1024 bits. Thus the elliptic curve group order n and the base field are large. The efficiency of these pairings becomes the bottleneck of the schemes. Existing solutions, such as converting composite-order pairings to prime-order ones or computing many pairings in parallel cannot solve the problem. The former is only valid for certain constructions and the latter is only helpful when many pairings are needed. In this paper, we make use of the huge number of threads available on Graphics Processing Units (GPUs) to speed up composite-order computation, both between pairings and within a single pairing. The experimental result shows that our method can speed up paring computation. Our method can also be ported to other platforms such as cloud systems.
机译:复合级双线性配对已应用于许多密码构造中,例如基于身份的加密,基于属性的加密和防泄漏弹性加密。但是,由于合成顺序至少应为1024位,因此这种配对的计算相对较慢。因此,椭圆曲线组阶数n和基场较大。这些配对的效率成为方案的瓶颈。现有的解决方案,例如将复合顺序配对转换为原始顺序配对或并行计算许多配对,都无法解决该问题。前者仅对某些结构有效,而后者仅在需要许多配对时才有用。在本文中,我们利用图形处理单元(GPU)上可用的大量线程来加速配对之间和单个配对内的复合顺序计算。实验结果表明,该方法可以加快算法的运算速度。我们的方法也可以移植到其他平台,例如云系统。

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