Inferring user height and improving impersonation attacks in mobile payments using a smartwatch
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 di...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2022
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| Summary: | 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%). |
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