User authentication using keystroke dynamics for cellular phones

Abstract

A new approach for keystroke-based authentication when using a cellular phone keypad as input device is presented. In the proposed method, users are authenticated using keystroke dynamics acquired when typing fixed alphabetic strings on a mobile phone keypad. The employed statistical classifier is able to perform user verification with an average equal error rate of about 13%. The obtained experimental results suggest that, when using mobile devices, a strong secure authentication scheme cannot rely on the sole keystroke dynamics, which however can be a module of a more complex system including, as basic security, a password-based protocol eventually hardened by keystroke analysis.

I Sensed It Was You: Authenticating Mobile Users with Sensor-Enhanced Keystroke Dynamics

“…Karatzouni and Clarke [27] reported comparable results on similar devices (12.2% EER). Campisi et al [12] analyzed a typing scenario with alphabetic strings on numeric keyboards and obtained a 13.59% EER using a statistical classifier. Hwang et al [24] reported accuracy improvements for short PIN lengths when using artificial rhythms and tempo cues.…”

“…[4] 1.45% F RR, 1.89% F AR Allows 1 authentication failure. [26] 3.80% EER [28] 7.10% EER Hardware (Mobile device) [13] 10.40% EER [27] 12.20% EER [12] 13.59% EER [24] 4.00% EER Use of artificial rhythms. [60] 0.00% F RR, 2.00% F AR Allows 1 authentication failure.…”

Keystroke Dynamics Overview

“…In this case, it is necessary to press several times the same key in order to obtain an alphabetical character. Campisi et al (2009) present a study on such a mobile phone. They argue that such authentication mechanism must be coupled with another one.…”

Making a good thing better: enhancing password/PIN-based user authentication with smartwatch

“…The study of keystroke dynamics was initially conducted on PCs and hardware keyboard (Bergadano et al 2002;Joyce and Gupta 1990;Kang et al 2007;Killourhy and Maxion 2010;Killourhy and Maxion 2009;Kotani and Horii 2005;Monrose and Rubin 1997;Monrose and Rubin 2000;Obaidat and Sadoun 1997;Peacock et al 2004). As mobile devices became increasingly popular, the research of keystroke dynamics switched to mobile devices (Campisi et al 2009;Clarke et al 2003;Hwang et al 2009;Karatzouni and Clarke 2007;Zahid et al 2009), and software keyboards (Huang et al 2012;Saevanee and Bhatarakosol 2008;Saevanee and Bhattarakosol 2009;Tasia et al 2014;Trojahn and Ortmeier 2012). Commercial products based on keystroke biometrics have been developed over the years (Id control 2018; Intensity analytics 2018; Keyboard biometrics -KeyTrac 2018; Plurilock Security Solutions Inc 2018).…”