Studying the performance of artificial neural networks on problems related to cryptography

被引：23

作者：

Laskari, E. C. ^{[1
]}

Meletiou, G. C.

Tasoulis, D. K.

Vrahatis, M. N.

机构：

[1] Univ Patras, Artificial Intelligence Res Ctr, GR-26110 Patras, Greece

[2] Univ Patras, Computat Intelligence Lab, Dept Math, GR-26110 Patras, Greece

[3] ATEI Epirus, GR-47100 Arta, Greece

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2006年 / 7卷 / 05期

关键词：

artificial neural networks; discrete logarithm; Diffie-Hellman problem; factorization; approximation;

D O I：

10.1016/j.nonrwa.2005.12.002

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Cryptosystems rely on the assumption that a number of mathematical problems are computationally intractable, in the sense that they cannot be solved in polynomial time. Numerous approaches have been applied to address these problems. In this paper, we consider artificial neural networks and study their performance on approximation problems related to cryptography. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：937 / 942

页数：6

共 35 条

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