Automated Annotation of Network Traffic with Data from Web Browser

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00358647" target="_blank" >RIV/68407700:21240/22:00358647 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Automated Annotation of Network Traffic with Data from Web Browser

Popis výsledku v původním jazyce

Encrypted traffic classification requires Machine Learning (ML) algorithms and a large amount of data to learn patterns and classify network communication without decrypting it. For the learning stage of ML models, we need a reliable and trusted dataset that delivers the ground truth for the whole classification. However, building a dataset is a very complicated and time-consuming task that stops ML to be used in the production environment of target networks. The aim of this work is to address this topic for network flow annotation using web traffic data. This paper introduces to problematics of network IP flow monitoring, analysis and classification. This problem is demonstrated on HTTP and HTTPS protocols. Moreover, this work describes a technique of data collection from web browsers and their pairing with traffic flows to create a reliable annotated dataset automatically

Název v anglickém jazyce

Automated Annotation of Network Traffic with Data from Web Browser

Popis výsledku anglicky

Encrypted traffic classification requires Machine Learning (ML) algorithms and a large amount of data to learn patterns and classify network communication without decrypting it. For the learning stage of ML models, we need a reliable and trusted dataset that delivers the ground truth for the whole classification. However, building a dataset is a very complicated and time-consuming task that stops ML to be used in the production environment of target networks. The aim of this work is to address this topic for network flow annotation using web traffic data. This paper introduces to problematics of network IP flow monitoring, analysis and classification. This problem is demonstrated on HTTP and HTTPS protocols. Moreover, this work describes a technique of data collection from web browsers and their pairing with traffic flows to create a reliable annotated dataset automatically

Druh

O - Ostatní výsledky

CEP obor

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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/VJ02010024" target="_blank" >VJ02010024: Analýza šifrovaného provozu pomocí síťových toků</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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