A user DNS fingerprint dataset

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F24%3A43909374" target="_blank" >RIV/60076658:12510/24:43909374 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21240/24:00377788

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2352340924003585" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352340924003585</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.dib.2024.110389" target="_blank" >10.1016/j.dib.2024.110389</a>

Result language

angličtina

Original language name

A user DNS fingerprint dataset

Original language description

Using a user DNS fingerprint allows one to identify a specific network user regardless of the knowledge of his IP address. This method is proper, for example, when examining the behavior of a monitored network user in more depth. In contrast to other studies, this work introduces a dataset for possible user identification based only on the knowledge of its DNS fingerprint created from the previously sent DNS queries. We created a large dataset from the real network traffic of a metropolitan Internet service provider. The dataset was created from 2.3 billion DNS queries representing 6.2 million different domain names. The data collection took place over three months from 12/2023 to 02/2024. The dataset contains a detailed user activity description in the sense of overall daily activity statistics and detailed 24 h activity statistics. Each dataset record contains a list of 1137 classification attributes. The absolutely unique feature of this data set is the classification of user activity based on categories of content accessed by a user. The new dataset can be used for the creation of machine learning models, allowing the identification of a specific user without direct knowledge of their IP addresses or additional network location information. The dataset can also serve as a reference dataset for the creation of DNS fingerprints of users. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY -NC license ( http://creativecommons.org/licenses/by-nc/4.0/ )

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

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

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

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

Name of the periodical

Data in Brief

ISSN

2352-3409

e-ISSN

—

Volume of the periodical

54

Issue of the periodical within the volume

June 2024

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

12

Pages from-to

1-12

UT code for WoS article

001235978600001

EID of the result in the Scopus database

2-s2.0-85190324602