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Cross-device tracking through identification of user typing behaviours
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Yuan, Hu, Maple, Carsten, Chen, Chao and Watson, Tim (2018) Cross-device tracking through identification of user typing behaviours. Electronics Letters, 54 (15). pp. 957-959. doi:10.1049/el.2018.0893 ISSN 0013-5194.
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Official URL: https://doi.org/10.1049/el.2018.0893
Abstract
A novel method of cross-device tracking based on user typing behaviours is presented. Compared with existing methods, typing behaviours can offer greater security and efficiency. When people type on their devices, a number of different factors may be considered to identify users, such as the angle and distance of contact point to the centre of the target character, the time elapsed between two typing actions and the physical force exerted on the device (which can be measured by an accelerometer). An experiment was conducted to validate the proposed model; those data are collected through an Android App developed for the purpose of this study. By collecting a reasonable amount of this type of data, it is shown that machine learning algorithms can be employed to first classify different users and subsequently authenticate users across devices.
| Item Type: | Journal Article | ||||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Journal or Publication Title: | Electronics Letters | ||||||||
| Publisher: | Institution of Engineering and Technology | ||||||||
| ISSN: | 0013-5194 | ||||||||
| Official Date: | 1 July 2018 | ||||||||
| Dates: |
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| Volume: | 54 | ||||||||
| Number: | 15 | ||||||||
| Page Range: | pp. 957-959 | ||||||||
| DOI: | 10.1049/el.2018.0893 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||
| Date of first compliant deposit: | 6 June 2018 | ||||||||
| Date of first compliant Open Access: | 22 October 2018 | ||||||||
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