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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