Publication Details

Pattern Detection Based Network Diagnostics

HOLKOVIČ, M.; BOHUŠ, M.; RYŠAVÝ, O. Pattern Detection Based Network Diagnostics. In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications. Setubal: SciTePress - Science and Technology Publications, 2020. p. 35-42. ISBN: 978-989-758-445-9.
Czech title
Diagnostika sítě založená na detekci vzorů
Type
conference paper
Language
English
Authors
Holkovič Martin, Ing., Ph.D.
Bohuš Michal, Ing.
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS)
Keywords

Network diagnostics, passive diagnostics, rule-based diagnostics, patterns lookup, patterns diagnostics, anomaly-based diagnostics.

Abstract

One of the most important parts of the network administrators' work is detecting and correcting errors inside computer networks. This part is also called network diagnostics. The problem is that computer networks are very complex, and there is no single universal approach for diagnosing the errors. In this paper, we propose a new method of diagnostics which utilizes looking for specific patterns inside captured network data. This approach automatically checks for all predefined patterns and generates a report with error descriptions for any detected errors. We have created a proof-of-concept tool and demonstrated its functionality.

Published
2020
Pages
35–42
Proceedings
Proceedings of the 17th International Joint Conference on e-Business and Telecommunications
ISBN
978-989-758-445-9
Publisher
SciTePress - Science and Technology Publications
Place
Setubal
DOI
UT WoS
000615962300002
EID Scopus
BibTeX
@inproceedings{BUT168132,
  author="Martin {Holkovič} and Michal {Bohuš} and Ondřej {Ryšavý}",
  title="Pattern Detection Based Network Diagnostics",
  booktitle="Proceedings of the 17th International Joint Conference on e-Business and Telecommunications",
  year="2020",
  pages="35--42",
  publisher="SciTePress - Science and Technology Publications",
  address="Setubal",
  doi="10.5220/0009891500350042",
  isbn="978-989-758-445-9",
  url="https://www.fit.vut.cz/research/publication/12293/"
}
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