Inferring user height and improving impersonation attacks in mobile payments using a smartwatch

Conference item

In this paper, we show that as a user makes mobile payments with a smartwatch, the height of the user can be inferred purely from inertial sensor data captured on the watch (with R 2 scores of up to 0.77). Besides unwanted information exposure, we also show that users of a similar height are more difficult to distinguish between in terms of their tap gesture data and that an attacker who chooses a victim of a similar height can improve the success chance of impersonation (by increasing the false acceptance rate by up to 20.6%).

Authors: Sturgess, J; Eberz, S; Sluganovic, I; Martinovic, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Host title: 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
• Pages: 775-780
• Publication date: 2022-05-06
• Acceptance date: 2022-01-16
• Event title: WristSense 2022: Workshop on Sensing Systems and Applications Using Wrist Worn Smart Devices (Co-located with IEEE PerCom)
• Event location: Pisa, Italy
• Event website: https://sites.google.com/view/wristsense2022/
• Event start date: 2022-03-21
• Event end date: 2022-03-25
• DOI: 10.1109/PerComWorkshops53856.2022.9767287
• EISBN: 978-1-6654-1647-4
• ISBN: 978-1-6654-1648-1
• Language: English
• Keywords: authentication; smartwatch; privacy; tap gesture; FFR