A novel dataset for encrypted virtual private network traffic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F23%3A43907124" target="_blank" >RIV/60076658:12310/23:43907124 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S235234092300063X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S235234092300063X?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.dib.2023.108945" target="_blank" >10.1016/j.dib.2023.108945</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A novel dataset for encrypted virtual private network traffic

Popis výsledku v původním jazyce

Encryption of network traffic should guarantee anonymity and prevent potential interception of information. Encrypted virtual private networks (VPNs) are designed to create special data tunnels that allow reliable transmission between networks and/or end users. However, as has been shown in a number of scientific papers, encryption alone may not be sufficient to secure data transmissions in the sense that certain information may be exposed. Our team has constructed a large dataset that contains generated encrypted network traffic data. This dataset contains a general network traffic model consisting of different types of network traffic such as web, emailing, video conferencing, video streaming, and ter-minal services. For the same network traffic model, data are measured for different scenarios, i.e., for data traffic through different types of VPNs and without VPNs. Additionally, the dataset contains the initial handshake of the VPN connec-tions. The dataset can be used by various data scientists deal-ing with the classification of encrypted network traffic and encrypted VPNs.

Název v anglickém jazyce

A novel dataset for encrypted virtual private network traffic

Popis výsledku anglicky

Encryption of network traffic should guarantee anonymity and prevent potential interception of information. Encrypted virtual private networks (VPNs) are designed to create special data tunnels that allow reliable transmission between networks and/or end users. However, as has been shown in a number of scientific papers, encryption alone may not be sufficient to secure data transmissions in the sense that certain information may be exposed. Our team has constructed a large dataset that contains generated encrypted network traffic data. This dataset contains a general network traffic model consisting of different types of network traffic such as web, emailing, video conferencing, video streaming, and ter-minal services. For the same network traffic model, data are measured for different scenarios, i.e., for data traffic through different types of VPNs and without VPNs. Additionally, the dataset contains the initial handshake of the VPN connec-tions. The dataset can be used by various data scientists deal-ing with the classification of encrypted network traffic and encrypted VPNs.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Data in Brief

ISSN

2352-3409

e-ISSN

—

Svazek periodika

47

Číslo periodika v rámci svazku

APR 2023

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

000947227400001

EID výsledku v databázi Scopus

2-s2.0-85150764470