About: Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In recent years, the cryptographic community has explored new approaches of power analysis based on machine learning models such as Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) or Random Forest (RF). Realized experiments proved that the method based on MLP can provide almost 100\% success rate after optimization. Nevertheless, this description of results is based on the first order success rate that is not enough satisfactory because this value can be deceiving. Moreover, the power analysis method based on MLP has not been compared with other well-known approaches such as template attacks or stochastic attacks yet. In this paper, we introduce the first fair comparison of power analysis attacks based on MLP and templates. The comparison is accomplished by using the identical data set and number of interesting points in power traces. We follow the unified framework for implemented side-channel attacks therefore we use guessing entropy as a metric of comparison. In recent years, the cryptographic community has explored new approaches of power analysis based on machine learning models such as Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) or Random Forest (RF). Realized experiments proved that the method based on MLP can provide almost 100\% success rate after optimization. Nevertheless, this description of results is based on the first order success rate that is not enough satisfactory because this value can be deceiving. Moreover, the power analysis method based on MLP has not been compared with other well-known approaches such as template attacks or stochastic attacks yet. In this paper, we introduce the first fair comparison of power analysis attacks based on MLP and templates. The comparison is accomplished by using the identical data set and number of interesting points in power traces. We follow the unified framework for implemented side-channel attacks therefore we use guessing entropy as a metric of comparison. (en)
Title	Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network (en)
skos:prefLabel	Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network Comparison of Profiling Power Analysis Attacks Using Templates and Multi-Layer Perceptron Network (en)
skos:notation	RIV/00216305:26220/14:PU111090!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 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	8159
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/14:PU111090
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Power Analysis, Neural Network, Template Attack, Comparison. (en)
http://linked.open.../riv/klicoveSlovo	Neural Network Comparison. Power Analysis Template Attack
http://linked.open...ontrolniKodProRIV	[B493D4CB60E2]
http://linked.open...v/mistoKonaniAkce	Atény
http://linked.open...i/riv/mistoVydani	Neuveden
http://linked.open...i/riv/nazevZdroje	Proceedings of the 1st International Conference on Mathematical Methods & Computational Techniques in Science & Engineering
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Malina, Lukáš Martinásek, Zdeněk
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-11-28 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Neuveden
https://schema.org/isbn	978-1-61804-256-9
http://localhost/t...ganizacniJednotka	26220

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software