Correlation Immunity of Boolean Functions: An Evolutionary Algorithms Perspective

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Stjepan Picek and Claude Carlet and 
                 Domagoj Jakobovic and Julian F. Miller and Lejla Batina",
  title =        "Correlation Immunity of Boolean Functions: An
                 Evolutionary Algorithms Perspective",
  booktitle =    "GECCO '15: Proceedings of the 2015 Annual Conference
                 on Genetic and Evolutionary Computation",
  year =         "2015",
  editor =       "Sara Silva and Anna I Esparcia-Alcazar and 
                 Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and 
                 Christine Zarges and Luis Correia and Terence Soule and 
                 Mario Giacobini and Ryan Urbanowicz and 
                 Youhei Akimoto and Tobias Glasmachers and 
                 Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and 
                 Marta Soto and Carlos Cotta and Francisco B. Pereira and 
                 Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and 
                 Heike Trautmann and Jean-Baptiste Mouret and 
                 Sebastian Risi and Ernesto Costa and Oliver Schuetze and 
                 Krzysztof Krawiec and Alberto Moraglio and 
                 Julian F. Miller and Pawel Widera and Stefano Cagnoni and 
                 JJ Merelo and Emma Hart and Leonardo Trujillo and 
                 Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and 
                 Carola Doerr",
  isbn13 =       "978-1-4503-3472-3",
  pages =        "1095--1102",
  keywords =     "genetic algorithms, genetic programming",
  month =        "11-15 " # jul,
  organisation = "SIGEVO",
  address =      "Madrid, Spain",
  URL =          "",
  DOI =          "doi:10.1145/2739480.2754764",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Boolean functions are essential in many stream
                 ciphers. When used in combiner generators, they need to
                 have sufficiently high values of correlation immunity,
                 alongside other properties. In addition, correlation
                 immune functions with small Hamming weight reduce the
                 cost of masking countermeasures against side-channel
                 attacks. Various papers have examined the applicability
                 of evolutionary algorithms for evolving cryptographic
                 Boolean functions. However, even when authors
                 considered correlation immunity, it was not given the
                 highest priority. Here, we examine the effectiveness of
                 three different EAs, namely, Genetic Algorithms,
                 Genetic Programming (GP) and Cartesian GP for evolving
                 correlation immune Boolean functions. Besides the
                 properties of balancedness and correlation immunity, we
                 consider several other relevant cryptographic
                 properties while maintaining the optimal trade-offs
                 among them. We show that evolving correlation immune
                 Boolean functions is an even harder objective than
                 maximizing nonlinearity.",
  notes =        "Also known as \cite{2754764} GECCO-2015 A joint
                 meeting of the twenty fourth international conference
                 on genetic algorithms (ICGA-2015) and the twentith
                 annual genetic programming conference (GP-2015)",

Genetic Programming entries for Stjepan Picek Claude Carlet Domagoj Jakobovic Julian F Miller Lejla Batina