Multi-objective evolution of hash functions for high speed networks

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{grochol:2017:CEC,
  author =       "David Grochol and Lukas Sekanina",
  booktitle =    "2017 IEEE Congress on Evolutionary Computation (CEC)",
  title =        "Multi-objective evolution of hash functions for high
                 speed networks",
  year =         "2017",
  editor =       "Jose A. Lozano",
  pages =        "1533--1540",
  address =      "Donostia, San Sebastian, Spain",
  publisher =    "IEEE",
  isbn13 =       "978-1-5090-4601-0",
  abstract =     "Hashing is a critical function in capturing and
                 analysis of network flows as its quality and execution
                 time influences the maximum throughput of network
                 monitoring devices. In this paper, we propose a
                 multi-objective linear genetic programming approach to
                 evolve fast and high-quality hash functions for common
                 processors. The search algorithm simultaneously
                 optimizes the quality of hashing and the execution
                 time. As it is very time consuming to obtain the real
                 execution time for a candidate solution on a particular
                 processor, the execution time is estimated in the
                 fitness function. In order to demonstrate the
                 superiority of the proposed approach, evolved hash
                 functions are compared with hash functions available in
                 the literature using real-world network data.",
  keywords =     "genetic algorithms, genetic programming, cryptography,
                 critical function, fitness function, hash functions,
                 hashing, high speed networks, multiobjective evolution,
                 multiobjective linear genetic programming, network
                 flows, network monitoring devices, real-world network
                 data, search algorithm, Hardware, Monitoring, Program
                 processors, Registers",
  isbn13 =       "978-1-5090-4601-0",
  DOI =          "doi:10.1109/CEC.2017.7969485",
  month =        "5-8 " # jun,
  notes =        "IEEE Catalog Number: CFP17ICE-ART Also known as
                 \cite{7969485}",
}

Genetic Programming entries for David Grochol Lukas Sekanina

Citations