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Using IMUs to identify supervisors on touch devices.

Lookup NU author(s): Dr Ahmed KharrufaORCiD, James Nicholson, Dr Paul Dunphy, Professor Stephen Hodges, Professor Pam Briggs, Professor Patrick OlivierORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Abstract

In addition to their popularity as personal devices, tablets, are becoming increasingly prevalent in work and public settings. In many of these application domains a supervisor user – such as the teacher in a classroom – oversees the function of one or more devices. Access to supervisory functions is typically controlled through the use of a passcode, but experience shows that keeping this passcode secret can be problematic. We introduce SwipeID, a method of identifying supervisor users across a set of touch-based devices by correlating data from a wrist-worn inertial measurement unit (IMU) and a corresponding touchscreen interaction. This approach naturally supports access at the time and point of contact and does not require any additional hardware on the client devices. We describe the design of our system and the challenge-response protocols we have considered. We then present an evaluation study to demonstrate feasibility. Finally we highlight the potential for our scheme to extend to different application domains and input devices.


Publication metadata

Author(s): Kharrufa A, Nicholson J, Dunphy P, Hodges S, Briggs P, Olivier P

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Human-Computer Interaction – INTERACT 2015

Year of Conference: 2015

Pages: 565-583

Online publication date: 30/08/2015

Acceptance date: 01/01/1900

Date deposited: 01/12/2015

ISSN: 0302-9743

Publisher: Springer

URL: http://dx.doi.org/10.1007/978-3-319-22668-2_44

DOI: 10.1007/978-3-319-22668-2_44

Notes: 15th IFIP TC 13 International Conference

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783319226675


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