Publication:
Public-key cryptography: a hardware implementation and novel neural network-based approach

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Authors
Nguyen, Phong
Subjects
Cryptography
Public-key
Secret-key
Discrete logarithm
Fast exponentiation
Diffie-Hellman
RSA
Inverse
GCD
Neural networks
Back-propagation
Sum of residues
Modulo reduciton
Advisors
Yang, Chyan
Date of Issue
1992-09
Date
September 1992
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
The concealment of information passed over a non-secure communication link lies in the complex field of cryptography. Furthermore, when absolutely no secure channel exists for the exchange of a secret key with which data in encrypted and decrypted, the remedy lies in a branch of cryptology known as public-key cryptosystem (PKS). This thesis provides an in-depth study of the public-key cryptosystem. Essential background knowledge is covered leading up to a VLSI implementation of a fast modulo exponentiator based on the sum of residues (SOR) method. Fast modulo exponentiation is vital in the most popular PKS schemes. Furthermore, since all cryptosystems make use of some form of mapping functions, a neural network - an excellent nonlinear mapping techniques - provides a viable medium upon which a possible cryptosystem can be based. In examining this possibility, this thesis presents an adaptation of the back-propagation neural network to a "pseudo" public-key arrangement. Following examination of the network, a key management system is then devised. Finally, a complete top-down block diagram of an entire cryptosystem based on the neural network of this study is proposed.
Type
Thesis
Description
Series/Report No
Department
Department of Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
98 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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