Language-independent gender identification through keystroke analysis

Ioannis Tsimperidis; Vasilios Katos; Nathan Clarke

doi:10.1108/ics-05-2014-0032

Language-independent gender identification through keystroke analysis

Ioannis Tsimperidis, Vasilios Katos^*, Nathan Clarke

^*Corresponding author for this work

School of Engineering, Computing and Mathematics

Democritus University of Thrace

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	286-301
Number of pages	0
Journal	Information & Computer Security
Volume	23
Issue number	3
DOIs	https://doi.org/10.1108/ics-05-2014-0032
Publication status	Published - 13 Jul 2015

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title = "Language-independent gender identification through keystroke analysis",

abstract = " 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. ",

author = "Ioannis Tsimperidis and Vasilios Katos and Nathan Clarke",

year = "2015",

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day = "13",

doi = "10.1108/ics-05-2014-0032",

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AB - 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.

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JO - Information & Computer Security

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Language-independent gender identification through keystroke analysis

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