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Fast Parallel Molecular Algorithms for DNA-Based Computation: Solving the Elliptic Curve Discrete Logarithm Problem over GF(2n)

机译:基于DNA的快速并行分子算法:求解GF(2n)上的椭圆曲线离散对数问题

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摘要

Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2n), n ∈ Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2n) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations.
机译:椭圆曲线密码算法将输入数据转换为无法识别的加密,并将无法识别的数据再次转换回其原始解密形式。这种加密形式的安全性取决于解决椭圆曲线离散对数问题(ECDLP)所需的巨大难度,特别是在GF(2 n ),n∈Z + < / sup>。本文介绍了一种通过分子计算机找到ECDLP解决方案的有效方法。我们认为这项研究成就将代表应用生物学计算的突破,并且本文证明了从原理上讲这是可能的。描述了三种基于DNA的算法:并行加法器,并行乘法器和GF(2 n )上的并行逆。所有这些算法的生物学运算时间都是关于n的多项式。考虑到此分析,使用公共密钥的加密可能不太安全。在这方面,本文的主要贡献是提供了分子计算解决此类雄心勃勃的计算潜力的增强证据。

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