Publication Details

A Fast FPGA-Based Classification of Application Protocols Optimized Using Cartesian GP

GROCHOL, D.; SEKANINA, L.; ŽÁDNÍK, M.; KOŘENEK, J. A Fast FPGA-Based Classification of Application Protocols Optimized Using Cartesian GP. In Applications of Evolutionary Computation, 18th European Conference. Lecture Notes in Computer Science. Berlin: Springer International Publishing, 2015. p. 67-78. ISBN: 978-3-319-16548-6.
Czech title
Rychlá Klasifikace Aplikačních Protokolů v FPGA Optimalizovaná Pomocí Kartezského Genetického Programování
Type
conference paper
Language
English
Authors
Keywords

computer network, cartesian genetic programming, classifier, FPGA

Abstract

This paper deals with design of an application protocol classifier intended for high speed networks operating at 100 Gbps. Because a very low latency is the main design constraint, the classifier is constructed as a combinational circuit in a field programmable gate array. The classification is performed using the first packet carrying the application payload. In order to further reduce the latency, the circuit is optimized by Cartesian genetic programming. Using a real network data, we demonstrated viability of our approach in task of a very fast classification of three application protocols (HTTP, SMTP, SSH).

Published
2015
Pages
67–78
Proceedings
Applications of Evolutionary Computation, 18th European Conference
Series
Lecture Notes in Computer Science
Volume
9028
ISBN
978-3-319-16548-6
Publisher
Springer International Publishing
Place
Berlin
DOI
EID Scopus
BibTeX
@inproceedings{BUT119801,
  author="David {Grochol} and Lukáš {Sekanina} and Martin {Žádník} and Jan {Kořenek}",
  title="A Fast FPGA-Based Classification of Application Protocols Optimized Using Cartesian GP",
  booktitle="Applications of Evolutionary Computation, 18th European Conference",
  year="2015",
  series="Lecture Notes in Computer Science",
  volume="9028",
  pages="67--78",
  publisher="Springer International Publishing",
  address="Berlin",
  doi="10.1007/978-3-319-16549-3\{_}6",
  isbn="978-3-319-16548-6",
  url="https://www.fit.vut.cz/research/publication/10772/"
}
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