2019
DOI: 10.1007/s12652-019-01654-y
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Strengthen user authentication on mobile devices by using user’s touch dynamics pattern

Abstract: Mobile devices, particularly the touch screen mobile devices, are increasingly used to store and access private and sensitive data or services, and this has led to an increased demand for more secure and usable security services, one of which is user authentication. Currently, mobile device authentication services mainly use a knowledge-based method, e.g. a PIN-based authentication method, and, in some cases, a fingerprint-based authentication method is also supported. The knowledgebased method is vulnerable t… Show more

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Cited by 32 publications
(33 citation statements)
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“…The primary source of input data in the case of a smartphone is the touchscreen, which enables performing various gestures, such as tapping, scrolling, swiping, etc. The way a user performs gestures depends on the user, which is often applied in user authentication [101][102][103]. Moreover, numerous factors, e.g., emotional state, device type, screen size, may affect gesture dynamics and shape even when they are performed by the same user.…”
Section: Touch Dynamicsmentioning
confidence: 99%
“…The primary source of input data in the case of a smartphone is the touchscreen, which enables performing various gestures, such as tapping, scrolling, swiping, etc. The way a user performs gestures depends on the user, which is often applied in user authentication [101][102][103]. Moreover, numerous factors, e.g., emotional state, device type, screen size, may affect gesture dynamics and shape even when they are performed by the same user.…”
Section: Touch Dynamicsmentioning
confidence: 99%
“…The experimental results indicate that the solution is highly accurate. Similarly, the authors in [26,27] analyzed the distinctness of touch dynamics for mobile authentication system. Trojahn et al [28] proposed an authentication scheme that is a combination of keystroke and handwriting based mechanisms through a touchscreen sensor.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Besides temporal data, finger pressure and area recorded by touchscreen devices have been exploited in most cases. Both features, but especially pressure, have shown discriminative capabilities better than timing characteristics in the vast majority of the works where they have been used [25,29,33,35,36], although results conflicting with this observation have been also reported [37]. SME signals collected by touchscreen devices also include TC, recorded at both key press and key release instants.…”
Section: Features Employed For Fixed Text Representationmentioning
confidence: 99%
“…Moreover, several studies have compared the discriminative capabilities of different kinds of features. As already mentioned in Section 4.1, the higher discriminative capability of finger pressure and area, with respect to timing information, has been for instance outlined in [25, 29, 33, 35, 36]. In more detail, finger pressure information has been typically reported as more relevant than finger area [28, 31].…”
Section: Performancementioning
confidence: 99%