k-Nearest Neighbors Algorithm in Profiling Power Analysis Attacks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU116424" target="_blank" >RIV/00216305:26220/16:PU116424 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.13164/re.2016.0365" target="_blank" >http://dx.doi.org/10.13164/re.2016.0365</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.13164/re.2016.0365" target="_blank" >10.13164/re.2016.0365</a>
Alternative languages
Result language
angličtina
Original language name
k-Nearest Neighbors Algorithm in Profiling Power Analysis Attacks
Original language description
Power analysis presents the typical example of successful attacks against trusted cryptographic devices such as RFID (Radio-Frequency IDentifications) and contact smart cards. In recent years, the cryptographic community has explored new approaches in power analysis based on machine learning models such as Support Vector Machine (SVM), RF (Random Forest) and Multi-Layer Perceptron (MLP). In this paper, we made an extensive comparison of machine learning algorithms in the power analysis. For this purpose, we implemented a verification program that always chooses the optimal settings of individual machine learning models in order to obtain the best classification accuracy. In our research, we used three datasets, the first contains the power traces of an unprotected AES (Advanced Encryption Standard) implementation. The second and third datasets are created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4). The obtained results revealed some interesting facts, namely, an elementary textit{k}-NN (textit{k}-Nearest Neighbors) algorithm, which has not been commonly used in power analysis yet, shows great application potential in practice.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Radioengineering
ISSN
1210-2512
e-ISSN
—
Volume of the periodical
1
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
19
Pages from-to
11-28
UT code for WoS article
000377231900020
EID of the result in the Scopus database
2-s2.0-85015616068