User Classification and Authentication for Mobile Device Based on Gesture Recognition

Intelligent mobile devices are now commonplace in daily life. A large amount of sensitive information is stored on these devices, raising severe concerns regarding data security. In this work, we propose a novel user classification and authentication scheme for mobile devices based on continuous ges...

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Bibliographic Details
Published inNetwork Science and Cybersecurity Vol. 55; pp. 125 - 135
Main Authors Nixon, Kent, Chen, Yiran, Mao, Zhi, Li, Kang
Format Reference Book Chapter
LanguageEnglish
Published United States Springer 2014
Springer New York
SeriesAdvances in Information Security
Subjects
Computer security
Data encryption
Electronics industry
Gesture Recognition
Mobile Device
Network hardware
Security Protection
Security Solution
Smart phones
Track Pattern
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Summary:Intelligent mobile devices are now commonplace in daily life. A large amount of sensitive information is stored on these devices, raising severe concerns regarding data security. In this work, we propose a novel user classification and authentication scheme for mobile devices based on continuous gesture recognition. The user’s input patterns are collected by the integrated sensors on an Android smartphone. A learning algorithm is developed to uniquely recognize a user during their normal interaction with the device while accommodating hardware and biometric features that are constantly changing. Our experimental results demonstrate a great possibility for our gesture-based security scheme to reach sufficient detection accuracy with an undetectable impact on user experience.
ISBN:1489990658
9781489990655
1461475961
9781461475965
ISSN:1568-2633
DOI:10.1007/978-1-4614-7597-2_8