Language-independent gender identification through keystroke analysis
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Authors: Tsimperidis, I., Katos, V. and Clarke, N.
Journal: Information and Computer Security
© Emerald Group Publishing Limited. Purpose - The purpose of this paper is to investigate the feasibility of identifying the gender of an author by measuring the keystroke duration when typing a message. Design/methodology/approach - Three classifiers were constructed and tested. The authors empirically evaluated the effectiveness of the classifiers by using empirical data. The authors used primary data as well as a publicly available dataset containing keystrokes from a different language to validate the language independence assumption. Findings - The results of this paper indicate that it is possible to identify the gender of an author by analyzing keystroke durations with a probability of success in the region of 70 per cent. Research limitations/implications - The proposed approach was validated with a limited number of participants and languages, yet the statistical tests show the significance of the results. However, this approach will be further tested with other languages. Practical implications - Having the ability to identify the gender of an author of a certain piece of text has value in digital forensics, as the proposed method will be a source of circumstantial evidence for "putting fingers on keyboard" and for arbitrating cases where the true origin of a message needs to be identified. Social implications - If the proposed method is included as part of a text-composing system (such as e-mail, and instant messaging applications), it could increase trust toward the applications that use it and may also work as a deterrent for crimes involving forgery. Originality/value - The proposed approach combines and adapts techniques from the domains of biometric authentication and data classification.