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Fastest Parallel Molecular Algorithms for the Elliptic Curve Discrete Logarithm Problem over GF(2n)

机译:GF(2n)上椭圆曲线离散对数问题的最快并行分子算法

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Cryptography based on Elliptic Curves (ECC) has emerged as an effective alternative to the existing public-key cryp-tosystems (RSA and DSA). Its success was due both to the fact that no fast algorithms were known to break it and that exceptional security levels could be obtained by using short keys. The Elliptic Curve Discrete Logarithm (ECDL) problem is the cornerstone of much of present-day ECCs. It was classified as a computationally intractable problem and, consequently, as a reliable and unbreakable cryptosystem. In a recent work, Li et al. built a molecular computer designed to solve it over GF(2n). It was based on two DNA-inspired algorithms: a parallel adder and a parallel multiplier, working in O(n) and O{n2) respectively, where n is the input size. In this paper, we first present two faster biological implementations, working in O(log(n)) and O(n · log(n)) respectively (worst case). Then, we propose our model as a reference parallel solution of the ECDL problem and finally we highlight the computational power of such nature-inspired paradigm.
机译:基于椭圆曲线(ECC)的密码术已成为现有公钥加密系统(RSA和DSA)的有效替代方法。它的成功是由于以下事实:没有已知的快速算法可以破解它,而且可以通过使用短键来获得出色的安全级别。椭圆曲线离散对数(ECDL)问题是当今许多ECC的基石。它被归类为计算上难以解决的问题,因此被归类为可靠且坚不可摧的密码系统。在最近的工作中,李等人。建立了一个分子计算机,旨在通过GF(2n)解决该问题。它基于两种受DNA启发的算法:并行加法器和并行乘法器,分别在O(n)和O {n2)中工作,其中n是输入大小。在本文中,我们首先介绍两种更快的生物学实现,分别在O(log(n))和O(n·log(n))下工作(最坏的情况)。然后,我们提出我们的模型作为ECDL问题的参考并行解决方案,最后我们强调这种自然灵感范式的计算能力。

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