Towards Provable Network Traffic Measurement and Analysis via
Semi-Labeled Trace Datasets

D 2018

Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets

ČERMÁK, Milan; Tomáš JIRSÍK; Petr VELAN; Jana KOMÁRKOVÁ; Stanislav ŠPAČEK et al.

Základní údaje

Originální název

Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets

Autoři

ČERMÁK, Milan; Tomáš JIRSÍK; Petr VELAN; Jana KOMÁRKOVÁ; Stanislav ŠPAČEK; Martin DRAŠAR a Tomáš PLESNÍK

Vydání

Vienna, Austria, 2018 Network Traffic Measurement and Analysis Conference (TMA), od s. 1-8, 8 s. 2018

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

IEEE, Conference

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14610/18:00106892

Organizační jednotka

Ústav výpočetní techniky

ISBN

978-3-903176-09-6

Klíčová slova anglicky

datasets;network traffic;analysis

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 18. 4. 2019 15:42, Mgr. Alena Mokrá

Anotace

V originále

Research in network traffic measurement and analysis is a long-lasting field with growing interest from both scientists and the industry. However, even after so many years, results replication, criticism, and review are still rare. We face not only a lack of research standards, but also inaccessibility of appropriate datasets that can be used for methods development and evaluation. Therefore, a lot of potentially high-quality research cannot be verified and is not adopted by the industry or the community. The aim of this paper is to overcome this controversy with a unique solution based on a combination of distinct approaches proposed by other research works. Unlike these studies, we focus on the whole issue covering all areas of data anonymization, authenticity, recency, publicity, and their usage for research provability. We believe that these challenges can be solved by utilization of semi-labeled datasets composed of real-world network traffic and annotated units with interest-related packet traces only. In this paper, we outline the basic ideas of the methodology from unit trace collection and semi-labeled dataset creation to its usage for research evaluation. We strive for this proposal to start a discussion of the approach and help to overcome some of the challenges the research faces today.

Návaznosti

VI20162019014, projekt VaV

Název: Simulace, detekce a potlačení kybernetických hrozeb ohrožujících kritickou infrastrukturu (Akronym: KYPO II)

Investor: Ministerstvo vnitra ČR, Simulace, detekce a potlačení kybernetických hrozeb ohrožujících kritickou infrastrukturu

Přiložené soubory

2018-TMA-towards-provable-network-traffic-measurement-analysis-semi-labeled-trace-datasets-presentation.pdf

2018-TMA-towards-provable-network-traffic-measurement-analysis-semi-labeled-trace-datasets-paper.pdf Verze souboru

Citovat

ČERMÁK, Milan; Tomáš JIRSÍK; Petr VELAN; Jana KOMÁRKOVÁ; Stanislav ŠPAČEK; Martin DRAŠAR a Tomáš PLESNÍK. Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets. Online. In 2018 Network Traffic Measurement and Analysis Conference (TMA). Vienna, Austria: IEEE, 2018, s. 1-8. ISBN 978-3-903176-09-6. Dostupné z: https://doi.org/10.23919/TMA.2018.8506498.

@inproceedings{1420697,
   author = {Čermák, Milan and Jirsík, Tomáš and Velan, Petr and Komárková, Jana and Špaček, Stanislav and Drašar, Martin and Plesník, Tomáš},
   address = {Vienna, Austria},
   booktitle = {2018 Network Traffic Measurement and Analysis Conference (TMA)},
   doi = {https://doi.org/10.23919/TMA.2018.8506498},
   keywords = {datasets;network traffic;analysis},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Vienna, Austria},
   isbn = {978-3-903176-09-6},
   pages = {1-8},
   publisher = {IEEE},
   title = {Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets},
   url = {http://tma.ifip.org/2018/wp-content/uploads/sites/3/2018/06/tma2018_paper1.pdf},
   year = {2018}
}

TY  - CONF
ID  - 1420697
AU  - Čermák, Milan - Jirsík, Tomáš - Velan, Petr - Komárková, Jana - Špaček, Stanislav - Drašar, Martin - Plesník, Tomáš
PY  - 2018
TI  - Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets
PB  - IEEE
CY  - Vienna, Austria
SN  - 9783903176096
KW  - datasets;network traffic;analysis
UR  - http://tma.ifip.org/2018/wp-content/uploads/sites/3/2018/06/tma2018_paper1.pdf
L2  - https://ieeexplore.ieee.org/document/8506498
N2  - Research in network traffic measurement and analysis is a long-lasting field with growing interest from both scientists and the industry. However, even after so many years, results replication, criticism, and review are still rare. We face not only a lack of research standards, but also inaccessibility of appropriate datasets that can be used for methods development and evaluation. Therefore, a lot of potentially high-quality research cannot be verified and is not adopted by the industry or the community. The aim of this paper is to overcome this controversy with a unique solution based on a combination of distinct approaches proposed by other research works. Unlike these studies, we focus on the whole issue covering all areas of data anonymization, authenticity, recency, publicity, and their usage for research provability. We believe that these challenges can be solved by utilization of semi-labeled datasets composed of real-world network traffic and annotated units with interest-related packet traces only. In this paper, we outline the basic ideas of the methodology from unit trace collection and semi-labeled dataset creation to its usage for research evaluation. We strive for this proposal to start a discussion of the approach and help to overcome some of the challenges the research faces today.
ER  -

ČERMÁK, Milan; Tomáš JIRSÍK; Petr VELAN; Jana KOMÁRKOVÁ; Stanislav ŠPAČEK; Martin DRAŠAR a Tomáš PLESNÍK. Towards Provable Network Traffic Measurement and Analysis via Semi-Labeled Trace Datasets. Online. In \textit{2018 Network Traffic Measurement and Analysis Conference (TMA)}. Vienna, Austria: IEEE, 2018, s.~1-8. ISBN~978-3-903176-09-6. Dostupné z: https://doi.org/10.23919/TMA.2018.8506498.

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