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IKDD: A Keystroke Dynamics Dataset for User Classification

Authors :
Ioannis Tsimperidis
Olga-Dimitra Asvesta
Eleni Vrochidou
George A. Papakostas
Source :
Information, Vol 15, Iss 9, p 511 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Keystroke dynamics is the field of computer science that exploits data derived from the way users type. It has been used in authentication systems, in the identification of user characteristics for forensic or commercial purposes, and to identify the physical and mental state of users for purposes that serve human–computer interaction. Studies of keystroke dynamics have used datasets created from volunteers recording fixed-text typing or free-text typing. Unfortunately, there are not enough keystroke dynamics datasets available on the Internet, especially from the free-text category, because they contain sensitive and personal information from the volunteers. In this work, a free-text dataset is presented, which consists of 533 logfiles, each of which contains data from 3500 keystrokes, coming from 164 volunteers. Specifically, the software developed to record user typing is described, the demographics of the volunteers who participated are given, the structure of the dataset is analyzed, and the experiments performed on the dataset justify its utility.

Details

Language :
English
ISSN :
20782489
Volume :
15
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Information
Publication Type :
Academic Journal
Accession number :
edsdoj.4f771f83e0b64d35bd62e910b604a5ce
Document Type :
article
Full Text :
https://doi.org/10.3390/info15090511