Language-independent gender identification through keystroke analysis. (13th July 2015)
- Record Type:
- Journal Article
- Title:
- Language-independent gender identification through keystroke analysis. (13th July 2015)
- Main Title:
- Language-independent gender identification through keystroke analysis
- Authors:
- Tsimperidis, Ioannis
Katos, Vasilios
Clarke, Nathan - Abstract:
- <abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Research limitations/implications</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Practical implications</title> <p> – Having the ability to identify the gender of an author of a certain piece of text has value<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Research limitations/implications</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Practical implications</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Social implications</title> <p> – 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. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The proposed approach combines and adapts techniques from the domains of biometric authentication and data classification.</p> </sec> </abstract> … (more)
- Is Part Of:
- Information and computer security. Volume 23:Number 3(2015)
- Journal:
- Information and computer security
- Issue:
- Volume 23:Number 3(2015)
- Issue Display:
- Volume 23, Issue 3 (2015)
- Year:
- 2015
- Volume:
- 23
- Issue:
- 3
- Issue Sort Value:
- 2015-0023-0003-0000
- Page Start:
- 286
- Page End:
- 301
- Publication Date:
- 2015-07-13
- Subjects:
- Computer security -- Management -- Periodicals
Computer networks -- Security measures -- Periodicals
Data protection -- Management -- Periodicals
658.47 - Journal URLs:
- http://www.emeraldinsight.com/loi/ics ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/ICS-05-2014-0032 ↗
- Languages:
- English
- ISSNs:
- 2056-4961
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4481.796000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3290.xml