On continuous user authentication via typing behavior
We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named typing behavior (TB) for continuous user authentication. Given a webc...
Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 23(2014), 10 vom: 10. Okt., Seite 4611-24 |
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Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2014
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Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
Schlagworte: | Journal Article |
Zusammenfassung: | We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named typing behavior (TB) for continuous user authentication. Given a webcam pointing toward a keyboard, we develop real-time computer vision algorithms to automatically extract hand movement patterns from the video stream. Unlike the typical continuous biometrics, such as keystroke dynamics (KD), TB provides a reliable authentication with a short delay, while avoiding explicit key-logging. We collect a video database where 63 unique subjects type static text and free text for multiple sessions. For one typing video, the hands are segmented in each frame and a unique descriptor is extracted based on the shape and position of hands, as well as their temporal dynamics in the video sequence. We propose a novel approach, named bag of multi-dimensional phrases, to match the cross-feature and cross-temporal pattern between a gallery sequence and probe sequence. The experimental results demonstrate a superior performance of TB when compared with KD, which, together with our ultrareal-time demo system, warrant further investigation of this novel vision application and biometric modality |
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Beschreibung: | Date Completed 29.09.2015 Date Revised 16.10.2014 published: Print Citation Status MEDLINE |
ISSN: | 1941-0042 |