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AES Embedded Hardware Implementation

Authors: Ould-cheikh Mourad; Si-Mohamed Lotfy; Noureddine Mehallegue; Ahmed Bouridane; Camel Tanougast;

AES Embedded Hardware Implementation

Abstract

The paper presents a parallel reconfigurable hardware implementation of the AES cryptographic algorithm developed for an embedded application. This new methodology directly maps a design described in a high level language, Handel-C, to FPGA platforms. The Handel-C approach narrows the gap between performance and flexibility, and thus, reduce the risk of translating a high level prototype into HDLs. It provides a high degree of flexibility from two viewpoints: the language level of abstraction and the hardware reconfiguration. Using Handel-C, we enhanced the performance of the designed unit by applying parallelism and reconfigurability. Our FPGA implementations show that superior performance can be achieved compared with software and hardware implementations counterparts. In particular, our design outperforms most of the other designs in speed. At the same time, the area cost for putting the AES algorithm on the same hardware core is also kept as low as possible.

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    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.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
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!
11
Average
Top 10%
Average
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