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GROCHOL, D. SEKANINA, L.
Original Title
Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing
Type
conference paper
Language
English
Original 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
Authors
GROCHOL, D.; SEKANINA, L.
Released
3. 9. 2020
Publisher
IEEE Computational Intelligence Society
Location
Los Alamitos
ISBN
978-1-7281-6929-3
Book
IEEE Congress on Evolutionary Computation
Pages from
1
Pages to
8
Pages count
URL
https://www.fit.vut.cz/research/publication/12169/
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/" }