The Keyboard Knows About You: Revealing User Characteristics via Keystroke Dynamics

Abstract

One of the causes of several problems on the internet, such as financial fraud, cyber-bullying, and seduction of minors, is the complete anonymity that a malicious user can maintain. Most methods that have been proposed to remove this anonymity are either intrusive, or violate privacy, or expensive. This paper proposes the recognition of certain characteristics of an unknown user through keystroke dynamics, which is the way a person is typing. The evaluation of the method consists of three stages: the acquisition of keystroke dynamics data from 118 volunteers during the daily use of their devices, the extraction and selection of keystroke dynamics features based on their information gain, and the testing of user characteristics recognition by training five well-known machine learning models. Experimental results show that it is possible to identify the gender, the age group, the handedness, and the educational level of an unknown user with high accuracy.