Assessing the effectiveness of artificial neural networks on problems related to elliptic curve cryptography

Cryptographic systems based on elliptic curves have been introduced as an alternative to conventional public key cryptosystems. The security of both kinds of cryptosystems relies on the hypothesis that the underlying mathematical problems are computationally intractable, in the sense that they canno...

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Veröffentlicht in:Mathematical and computer modelling Jg. 46; H. 1; S. 174 - 179
Hauptverfasser: Laskari, E.C., Meletiou, G.C., Stamatiou, Y.C., Tasoulis, D.K., Vrahatis, M.N.
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.07.2007
Elsevier Science
Schlagworte:
Algebra
Algebraic geometry
Artificial neural networks
Boolean functions
Discrete logarithm
Elliptic curves
Exact sciences and technology
Mathematical analysis
Mathematics
Methods of scientific computing (including symbolic computation, algebraic computation)
Number theory
Numerical analysis. Scientific computation
Partial differential equations
Sciences and techniques of general use
Boolean functions
Elliptic curves
Discrete logarithm
Artificial neural networks
Polynomial
Neural computation
Boolean function
Elliptic curve
Neural network
Partial differential equation
Polynomial time
Elliptic equation
Scientific computation
Applied mathematics
Cryptography
Mathematical model
Computer aided analysis
ISSN:0895-7177, 1872-9479
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Zusammenfassung:Cryptographic systems based on elliptic curves have been introduced as an alternative to conventional public key cryptosystems. The security of both kinds of cryptosystems relies on the hypothesis that the underlying mathematical problems are computationally intractable, in the sense that they cannot be solved in polynomial time. In this paper, we study the performance of artificial neural networks on the computation of a Boolean function derived from the use of elliptic curves in cryptographic applications.
ISSN:0895-7177
1872-9479
DOI:10.1016/j.mcm.2006.12.017