In the relatively recent past, the analysis of keystroke dynamics for biometric recognition purposes has intrigued researchers, since practical evidences have shown differences in the typing behaviours of distinct subjects. This area of research has become even more appealing since the emergence and evolution of mobile smartphones, given their pervasiveness and intensive use in real‐life applications. In addition, unlike hard keyboards used with computers, mobile smartphones offer the possibility of exploiting embedded sensors to augment the information acquired when typing on their soft keyboards. This study discusses the state of the art of keystroke‐dynamics‐based automatic recognition system, exclusively when dealing with mobile devices, for both verification and identification purposes. In more details, the databases employed, the features selected, the methodologies implemented, and the performance achieved through the technological advances introduced in the last years, are here overviewed.

Maiorana, E., Kalita, H., Campisi, P. (2020). Mobile keystroke dynamics for biometric recognition: An overview. IET BIOMETRICS [10.1049/bme2.12003].

Mobile keystroke dynamics for biometric recognition: An overview

Maiorana, Emanuele
;
Kalita, Himanka;Campisi, Patrizio
2020

Abstract

In the relatively recent past, the analysis of keystroke dynamics for biometric recognition purposes has intrigued researchers, since practical evidences have shown differences in the typing behaviours of distinct subjects. This area of research has become even more appealing since the emergence and evolution of mobile smartphones, given their pervasiveness and intensive use in real‐life applications. In addition, unlike hard keyboards used with computers, mobile smartphones offer the possibility of exploiting embedded sensors to augment the information acquired when typing on their soft keyboards. This study discusses the state of the art of keystroke‐dynamics‐based automatic recognition system, exclusively when dealing with mobile devices, for both verification and identification purposes. In more details, the databases employed, the features selected, the methodologies implemented, and the performance achieved through the technological advances introduced in the last years, are here overviewed.
Maiorana, E., Kalita, H., Campisi, P. (2020). Mobile keystroke dynamics for biometric recognition: An overview. IET BIOMETRICS [10.1049/bme2.12003].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/375844
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