Citation
M. Abulkhirat, Esam
(2003)
Enhancing speed performance of the cryptographic algorithm based on the lucas sequence.
Masters thesis, Universiti Putra Malaysia.
Abstract
Computer information and network security has recently become a popular subject
due to the explosive growth of the Internet and the migration of commerce practices
to the electronic medium. Thus the authenticity and privacy of the information transmitted
and the data stored on networked computers is of utmost importance. The
deployment of network security procedures requires the implementation of cryptographic
functions. More specifically, these include encryption, decryption, authentication,
digital signature algorithms and message-digest functions. Performance has
always been the most critical characteristic of a cryptographic function, which determines
its effectiveness.Since the discovery of public-key cryptography, very few convincingly secure asymmetric
schemes have been discovered despite considerable research efforts. Utilizing
the properties of Lucas functions introduced a public key system based on Lucas functions
instead of exponentiation, which offer a good alternative to the most publicly
used exponential public key system RSA.
LUC cryptosystem algorithm based on the quadratic and cubic polynomial, is
introduced in this thesis with a new formula to distinguishing between the cubic
polynomial roots. Reducing the calculation time of the algorithm, in sequential and
parallel platforms, using the doubling-rule technique combined with a new scheme
led to a strong improvement of the LUC algorithm speed.
The computation time analysis shows that whene doubling with remainder technique
is used, the improvement of the speed rises rapidly compared to the standard
implementation of the LUC algorithm and LUC algorithm with doubling rule. Furthermore
the algorithm is still keeping its simplicity of non-multiplicative and nonexponentiation
public-key cryptosystem. The improved algorithm is applied on the
lab-PC for the sequential platform, and cluster-computing machine for the parallel
platform, which lead to a substantial time reduction and an enhancement of the
algorithm speed in both platforms.
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