TIPS: context-aware implicit user identification using touch screen in uncontrolled environments

Authors:
Tao Feng;Jun Yang;Zhixian Yan;Emmanuel Munguia Tapia;Weidong Shi
Affiliations:
University of Houston;Samsung Research America;Samsung Research America;Samsung Research America;University of Houston
Venue:
Proceedings of the 15th Workshop on Mobile Computing Systems and Applications
Year:
2014

Citing 7
Cited 0

Implicit authentication for mobile devices

HotSec'09 Proceedings of the 4th USENIX conference on Hot topics in security
SpeakerSense: energy efficient unobtrusive speaker identification on mobile phones

Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
SenGuard: Passive user identification on smartphones using multiple sensors

WIMOB '11 Proceedings of the 2011 IEEE 7th International Conference on Wireless and Mobile Computing, Networking and Communications
Biometric-rich gestures: a novel approach to authentication on multi-touch devices

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Touch me once and i know it's you!: implicit authentication based on touch screen patterns

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Secure unlocking of mobile touch screen devices by simple gestures: you can see it but you can not do it

Proceedings of the 19th annual international conference on Mobile computing & networking
SilentSense: silent user identification via touch and movement behavioral biometrics

Proceedings of the 19th annual international conference on Mobile computing & networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

Due to the dramatical increase in popularity of mobile devices in the last decade, more sensitive user information is stored and accessed on these devices everyday. However, most existing technologies for user authentication only cover the login stage or only work in restricted controlled environments or GUIs in the post login stage. In this work, we present TIPS, a Touch based Identity Protection Service that implicitly and unobtrusively authenticates users in the background by continuously analyzing touch screen gestures in the context of a running application. To the best of our knowledge, this is the first work to incorporate contextual app information to improve user authentication. We evaluate TIPS over data collected from 23 phone owners and deployed it to 13 of them with 100 guest users. TIPS can achieve over 90% accuracy in real-life naturalistic conditions within a small amount of computational overhead and 6% of battery usage.