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Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU132248" target="_blank" >RIV/00216305:26230/19:PU132248 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fit.vut.cz/research/publication/11918/" target="_blank" >https://www.fit.vut.cz/research/publication/11918/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-16670-0_15" target="_blank" >10.1007/978-3-030-16670-0_15</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions

  • Original language description

    The ever-increasing need for information security requires a constant refinement of contemporary ciphers. One of these are stream ciphers which secure data by utilizing a pseudo-randomly generated binary sequence. Generating a cryptographically secure sequence is not an easy task and requires a Boolean function possessing multiple cryptographic properties. One of the most successful ways of designing these functions is genetic programming. In this paper, we present a comparative study of three genetic programming methods, tree-based, Cartesian and linear, on the task of generating Boolean functions with an even number of inputs possessing good values of nonlinearity, balancedness, correlation immunity, and algebraic degree. Our results provide a comprehensive overview of how genetic programming methods compare when designing functions of different sizes, and we show that linear genetic programming, which has not been used for design of some of these functions before, is the best at dealing with increasing number of inputs, and creates desired functions with better reliability than the commonly used methods.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA19-10137S" target="_blank" >GA19-10137S: Designing and exploiting libraries of approximate circuits</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Genetic Programming 22st European Conference, EuroGP 2019, Proceedings

  • ISBN

    978-3-030-14811-9

  • ISSN

  • e-ISSN

  • Number of pages

    17

  • Pages from-to

    228-244

  • Publisher name

    Springer International Publishing

  • Place of publication

    Cham

  • Event location

    Leipzig

  • Event date

    Apr 24, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article