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https://doi.org/10.32657/10220...
Doctoral thesis . 2019 . Peer-reviewed
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Optimising implementation of block ciphers

Authors: Tan, Quan Quan;

Optimising implementation of block ciphers

Abstract

With the increasing need to protect information digitally, the study of cryptography has become of paramount importance. The digital world requires strong and efficient encryption algorithms in order to ensure private information are not compromised. As we strive towards making our devices smaller, the cost of the cryptographic implementation becomes more significant. In this thesis, we will look at new optimising algorithms to reduce the number of exclusive or (XOR) boolean operations in the workhorses algorithms for encryption. The algorithms presented in this thesis are new and based on an improved version of the Boyar and Peralta's algorithm. It was motivated by a graph search approach to find a path towards the various targets. We will be drawing comparisons to the results obtained by various algorithms out there such as Paar's algorithm, Boyar and Peralta's algorithm. Overall, the results obtained from the new heuristic showed that this algorithm fares better than those mentioned above. Master of Science

Country
Singapore
Related Organizations
Keywords

Science::Mathematics::Discrete mathematics::Cryptography, 004, :Mathematics::Discrete mathematics::Cryptography [Science]

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
bronze