Abstract
This work investigates how context should be taken into account when performing continuous authentication of a smartphone user based on touchscreen and accelerometer readings extracted from swipe gestures. The study is conducted on the publicly available HMOG dataset consisting of 100 study subjects performing pre-defined reading and navigation tasks while sitting and walking. It is shown that context-specific models are needed for different smartphone usage and human activity scenarios to minimize authentication error. Also, the experimental results suggests that utilization of phone movement improves swipe gesture-based verification performance only when the user is moving.
| Original language | English |
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| Title of host publication | ESANN 2018 - Proceedings |
| Subtitle of host publication | 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning |
| Publisher | i6doc.com |
| Pages | 639-644 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-287587047-6 |
| Publication status | Published - 1 Jan 2018 |
| MoE publication type | A4 Article in a conference publication |
| Event | 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2018 - Bruges, Belgium Duration: 25 Apr 2018 → 27 Apr 2018 |
Conference
| Conference | 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2018 |
|---|---|
| Country/Territory | Belgium |
| City | Bruges |
| Period | 25/04/18 → 27/04/18 |