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Profiling Power Analysis Attack Based on Multi-Layer Perceptron Network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU115950" target="_blank" >RIV/00216305:26220/15:PU115950 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-319-15765-8_18" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-15765-8_18</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-15765-8_18" target="_blank" >10.1007/978-3-319-15765-8_18</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Profiling Power Analysis Attack Based on Multi-Layer Perceptron Network

  • Original language description

    In 2013, an innovative method of power analysis was presented. Realized experiments proved that the proposed method based on Multi-Layer Perceptron (MLP) can provide almost 100 percent success rate. This description based on the first-order success rate is not appropriate enough. Moreover, the above mentioned works contain other lacks: the MLP has not been compared with other well-known attacks, an adversary uses too many points of power trace and a general description of the MLP method was not provided. In this paper, we eliminate these weaknesses by introducing the first fair comparison of power analysis attacks based on the MLP and templates. The comparison is accomplished by using the identical data sets, number of interesting points and guessing entropy as a metric. The first data set created contains the power traces of an unprotected AES implementation in order to classify the secret key stored. The second and third data sets were created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4). Secret offset is revealed depending on the number of interesting points and power traces in this experiment. Moreover, we create a general description of the MLP attack.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Book/collection name

    Computational Problems in Science and Engineering

  • ISBN

    978-3-319-15764-1

  • Number of pages of the result

    25

  • Pages from-to

    1-25

  • Number of pages of the book

    491

  • Publisher name

    Springer International Publishing

  • Place of publication

    Switzerland 2015

  • UT code for WoS chapter