Automated Annotation of Network Traffic with Data from Web Browser

Result code in 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>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Automated Annotation of Network Traffic with Data from Web Browser

Original language description

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

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

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

Project

<a href="/en/project/VJ02010024" target="_blank" >VJ02010024: Flow-based Encrypted Traffic Analysis</a><br>

Continuities

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

Publication year

2022

Confidentiality

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