Result Details

Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing

GROCHOL, D.; SEKANINA, L. Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing. In IEEE Congress on Evolutionary Computation. Los Alamitos: IEEE Computational Intelligence Society, 2020. p. 1-8. ISBN: 978-1-7281-6929-3.
Type
conference paper
Language
English
Authors
Abstract

Fast and high-quality network flow hashing is an essential operation in many high-speed network systems such as network monitoring probes. We propose a multi-objective evolutionary design method capable of evolving hash functions for IPv4 and IPv6 flow hashing. Our approach combines Cartesian genetic programming (CGP) with Non-dominated sorting genetic algorithm II (NSGA-II) and aims to optimize not only the quality of hashing, but also the execution time of the hash function. The evolved hash functions are evaluated on real data sets collected in computer network and compared against other evolved and conventionally created  hash functions.

Keywords

Cartesian genetic programming, linear genetic programming, hash function, network flow, Internet protocol

Published
2020
Pages
1–8
Proceedings
IEEE Congress on Evolutionary Computation
Conference
IEEE Congress on Evolutionary Computation
ISBN
978-1-7281-6929-3
Publisher
IEEE Computational Intelligence Society
Place
Los Alamitos
DOI
UT WoS
000703998201109
EID Scopus
BibTeX
@inproceedings{BUT168244,
  author="David {Grochol} and Lukáš {Sekanina}",
  title="Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing",
  booktitle="IEEE Congress on Evolutionary Computation",
  year="2020",
  pages="1--8",
  publisher="IEEE Computational Intelligence Society",
  address="Los Alamitos",
  doi="10.1109/CEC48606.2020.9185723",
  isbn="978-1-7281-6929-3",
  url="https://www.fit.vut.cz/research/publication/12169/"
}
Files
Projects
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, start: 2016-01-01, end: 2020-12-31, completed
Research groups
Departments
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