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- W4229072570 abstract "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<sup>2</sup> 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%)." @default.
- W4229072570 created "2022-05-08" @default.
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- W4229072570 date "2022-03-21" @default.
- W4229072570 modified "2023-09-29" @default.
- W4229072570 title "Inferring User Height and Improving Impersonation Attacks in Mobile Payments using a Smartwatch" @default.
- W4229072570 doi "https://doi.org/10.1109/percomworkshops53856.2022.9767287" @default.
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