About: Optimization of Power Analysis Using Neural Network

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In power analysis, many different statistical methods and power consumption models are used to obtain the value of a secret key from the power traces measured. An interesting method of power analysis based on multi-layer perceptron claiming a $90\%$ success rate. The theoretical and empirical success rates were determined to be $80\%$ and $85\%$, respectively, which is not sufficient enough. In the paper, we propose and realize an optimization of this power analysis method which improves the success rate to almost $100\%$. The optimization is based on preprocessing the measured power traces using the calculation of the average trace and the subsequent calculation of the difference power traces. In this way, the prepared power patterns were used for neural network training and of course during the attack. This optimization is computationally undemanding compared to other methods of preprocessing usually applied in power analysis, and has a great impact on classification results. In the paper, we compar In power analysis, many different statistical methods and power consumption models are used to obtain the value of a secret key from the power traces measured. An interesting method of power analysis based on multi-layer perceptron claiming a $90\%$ success rate. The theoretical and empirical success rates were determined to be $80\%$ and $85\%$, respectively, which is not sufficient enough. In the paper, we propose and realize an optimization of this power analysis method which improves the success rate to almost $100\%$. The optimization is based on preprocessing the measured power traces using the calculation of the average trace and the subsequent calculation of the difference power traces. In this way, the prepared power patterns were used for neural network training and of course during the attack. This optimization is computationally undemanding compared to other methods of preprocessing usually applied in power analysis, and has a great impact on classification results. In the paper, we compar (en)
Title	Optimization of Power Analysis Using Neural Network Optimization of Power Analysis Using Neural Network (en)
skos:prefLabel	Optimization of Power Analysis Using Neural Network Optimization of Power Analysis Using Neural Network (en)
skos:notation	RIV/00216305:26220/14:PU109604!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita	S
http://linked.open...avai/riv/aktivity	S
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Martinásek, Zdeněk Hajný, Jan Malina, Lukáš
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	34970
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/14:PU109604
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Power analysis, neural network, optimization, preprocessing. (en)
http://linked.open.../riv/klicoveSlovo	Power analysis neural network optimization preprocessing.
http://linked.open...ontrolniKodProRIV	[467442469FF8]
http://linked.open...v/mistoKonaniAkce	Berlín
http://linked.open...i/riv/mistoVydani	Neuveden
http://linked.open...i/riv/nazevZdroje	Smart Card Research and Advanced Applications, Lecture Notes in Computer Science
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Hajný, Jan Malina, Lukáš Martinásek, Zdeněk
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-11-27 (xsd:date)
number of pages	14 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-319-08302-5
http://localhost/t...ganizacniJednotka	26220

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