Analysis of Statistical Distribution Changes of Input Features in Network Traffic Classification Domain

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F24%3A10133690" target="_blank" >RIV/63839172:_____/24:10133690 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21240/24:00375887

Result on the web

<a href="https://ieeexplore.ieee.org/document/10575630" target="_blank" >https://ieeexplore.ieee.org/document/10575630</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/NOMS59830.2024.10575630" target="_blank" >10.1109/NOMS59830.2024.10575630</a>

Result language

angličtina

Original language name

Analysis of Statistical Distribution Changes of Input Features in Network Traffic Classification Domain

Original language description

This study investigates the evolving landscape of network traffic monitoring, which is crucial for maintaining computer network services and security. Traditional methods like Deep Packet Inspection (DPI) face challenges due to increased privacy protection through encryption, prompting a shift towards statistical-based detection using Machine Learning (ML). On the other hand, ML struggles with long-term evaluation due to various distribution changes. This study focuses on the CESNET-TLS-Year22 dataset, derived from one year of TLS network traffic on the CESNET2 backbone. Described research explores the behavior of modern protocols in real-world scenarios and their impact on dataset quality. The main result of our analysis is the identification of the Weekend phenomenon in network traffic classification that is generally overlooked during ML model training.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2024

Confidentiality

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

Article name in the collection

NOMS 2024-2024 IEEE Network Operations and Management Symposium

ISBN

979-8-3503-2793-9

ISSN

2374-9709

e-ISSN

—

Number of pages

6

Pages from-to

—

Publisher name

IEEE

Place of publication

New York

Event location

Seoul, South Korea

Event date

May 6, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001270140300155