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

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.