CESNET Idle OS Traffic: A Dataset of Idle Traffic of Various Operating Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F25%3A10133775" target="_blank" >RIV/63839172:_____/25:10133775 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21240/25:00386674

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/11297565" target="_blank" >https://ieeexplore.ieee.org/document/11297565</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23919/CNSM67658.2025.11297565" target="_blank" >10.23919/CNSM67658.2025.11297565</a>

Jazyk výsledku

angličtina

Název v původním jazyce

CESNET Idle OS Traffic: A Dataset of Idle Traffic of Various Operating Systems

Popis výsledku v původním jazyce

Machine learning methods in networking research critically depend on the availability of high-quality datasets. While several network traffic datasets exist, they typically focus on backbone traffic, intrusion scenarios, or application behavior, containing a mix of many types of traffic. In this paper, we introduce the CESNET Idle OS Traffic dataset. It contains traffic traces of various operating system in the &quot;idle&quot; state, i.e. without any user interaction, captured in a controlled lab environment. The primary intended use of the dataset is to support research of operating system fingerprinting, but it can also be used to enhance dataset for anomaly and intrusion detection, in forensic analysis, or education. We also release the toolset used to create the dataset, which enable researchers to replicate the measurement process or extend the dataset with additional operating systems.

Název v anglickém jazyce

CESNET Idle OS Traffic: A Dataset of Idle Traffic of Various Operating Systems

Popis výsledku anglicky

Machine learning methods in networking research critically depend on the availability of high-quality datasets. While several network traffic datasets exist, they typically focus on backbone traffic, intrusion scenarios, or application behavior, containing a mix of many types of traffic. In this paper, we introduce the CESNET Idle OS Traffic dataset. It contains traffic traces of various operating system in the &quot;idle&quot; state, i.e. without any user interaction, captured in a controlled lab environment. The primary intended use of the dataset is to support research of operating system fingerprinting, but it can also be used to enhance dataset for anomaly and intrusion detection, in forensic analysis, or education. We also release the toolset used to create the dataset, which enable researchers to replicate the measurement process or extend the dataset with additional operating systems.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LM2023054" target="_blank" >LM2023054: e-Infrastruktura CZ</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2025 21st International Conference on Network and Service Management (CNSM)

ISBN

978-3-903176-75-1

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

IEEE

Místo vydání

Neuveden

Místo konání akce

Bologna, Itálie

Datum konání akce

27. 10. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—