A user DNS fingerprint dataset
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 possi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-06-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924003585 |
| _version_ | 1797203052650823680 |
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| author | Josef Zápotocký Jan Fiala Jan Fesl |
| author_facet | Josef Zápotocký Jan Fiala Jan Fesl |
| author_sort | Josef Zápotocký |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-24T08:13:12Z |
| format | Article |
| id | doaj.art-c12cda577485463c85c901b61dab1f23 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-24T08:13:12Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-c12cda577485463c85c901b61dab1f232024-04-17T04:49:18ZengElsevierData in Brief2352-34092024-06-0154110389A user DNS fingerprint datasetJosef Zápotocký0Jan Fiala1Jan Fesl2Department of Computer Systems, Faculty of Information Technology, Czech Technical University in Prague, Czech RepublicDepartment of Applied Mathematics and Informatics, Faculty of Economics, University of South Bohemia in České Budějovice, Czech RepublicDepartment of Computer Systems, Faculty of Information Technology, Czech Technical University in Prague, Czech Republic; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S2352340924003585DNSUserMachine learningIdentificationFingerprint |
| spellingShingle | Josef Zápotocký Jan Fiala Jan Fesl A user DNS fingerprint dataset Data in Brief DNS User Machine learning Identification Fingerprint |
| title | A user DNS fingerprint dataset |
| title_full | A user DNS fingerprint dataset |
| title_fullStr | A user DNS fingerprint dataset |
| title_full_unstemmed | A user DNS fingerprint dataset |
| title_short | A user DNS fingerprint dataset |
| title_sort | user dns fingerprint dataset |
| topic | DNS User Machine learning Identification Fingerprint |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924003585 |
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