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Keystroke Dynamics as a Language Profiling Tool: Identifying Mother Tongue of Unknown Internet Users

Authors :
Ioannis Tsimperidis
Denitsa Grunova
Soumen Roy
Lefteris Moussiades
Source :
Telecom, Vol 4, Iss 3, Pp 369-377 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Understanding the distinct characteristics of unidentified Internet users is helpful in various contexts, including digital forensics, targeted advertising, and user interaction with services and systems. Keystroke dynamics (KD) enables the analysis of data derived from a user’s typing behaviour on a keyboard as one approach to obtain such information. This study conducted experiments on a developed dataset that recorded samples of typing in five different mother tongues to determine Internet users’ mother tongue. Based on only a few KD features and machine learning techniques, 82% accuracy was achieved in recognising an unknown user’s mother tongue. This research highlights the potential for KD as a reliable method for identifying the mother tongue of Internet users, with implications for various applications such as improving digital forensic investigations, targeted advertising strategies, and optimising user experiences with online services.

Details

Language :
English
ISSN :
26734001
Volume :
4
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Telecom
Publication Type :
Academic Journal
Accession number :
edsdoj.0c1d4fa62bef4bd7a00265f220dfe685
Document Type :
article
Full Text :
https://doi.org/10.3390/telecom4030021