Abstract
| Original language | English |
|---|---|
| Title of host publication | IEEE International Conference on Pervasive Computing and Communications |
| Subtitle of host publication | PerCom 2015 |
| Publisher | IEEE |
| Pages | 189-197 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781479980338 |
| ISBN (Print) | 9781479980345 |
| DOIs | |
| Publication status | Published - Mar 2015 |
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Keywords
- mobile devices
- authentication
- sensor data
- battery consumption
- global positioning system,
Cite this
}
Sensor use and usefulness: trade-offs for data-driven authentication on mobile devices. / Micallef, Nicholas; Kayacik, Hilmi Gunes; Just, Michael; Baillie, Lynne; Aspinall, David.
IEEE International Conference on Pervasive Computing and Communications : PerCom 2015. IEEE, 2015. p. 189-197.Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)
TY - CHAP
T1 - Sensor use and usefulness: trade-offs for data-driven authentication on mobile devices
AU - Micallef, Nicholas
AU - Kayacik, Hilmi Gunes
AU - Just, Michael
AU - Baillie, Lynne
AU - Aspinall, David
PY - 2015/3
Y1 - 2015/3
N2 - Modern mobile devices come with an array of sensors that support many interesting applications. However, sensors have different sampling costs (e.g., battery drain) and benefits (e.g., accuracy) under different circumstances. In this work we investigate the trade-off between the cost of using a sensor and the benefit gained from its use, with application to data-driven authentication on mobile devices. Current authentication practice, where user behaviour is first learned from the sensor data and then used to detect anomalies, typically assumes a fixed sampling rate and does not consider the battery consumption and usefulness of sensors. In this work we study how battery consumption and sensor effectiveness (e.g., for detecting attacks) vary when using different sensors and different sensor sampling rates. We use data from both controlled lab studies, as well as field trials, for our experiments. We also propose an adaptive sampling technique that adjusts the sampling rate based on an expected device vigilance level. Our results show that it is possible to reduce the battery consumption tenfold without significantly impacting the detection of attacks.
AB - Modern mobile devices come with an array of sensors that support many interesting applications. However, sensors have different sampling costs (e.g., battery drain) and benefits (e.g., accuracy) under different circumstances. In this work we investigate the trade-off between the cost of using a sensor and the benefit gained from its use, with application to data-driven authentication on mobile devices. Current authentication practice, where user behaviour is first learned from the sensor data and then used to detect anomalies, typically assumes a fixed sampling rate and does not consider the battery consumption and usefulness of sensors. In this work we study how battery consumption and sensor effectiveness (e.g., for detecting attacks) vary when using different sensors and different sensor sampling rates. We use data from both controlled lab studies, as well as field trials, for our experiments. We also propose an adaptive sampling technique that adjusts the sampling rate based on an expected device vigilance level. Our results show that it is possible to reduce the battery consumption tenfold without significantly impacting the detection of attacks.
KW - mobile devices
KW - authentication
KW - sensor data
KW - battery consumption
KW - global positioning system,
U2 - 10.1109/PERCOM.2015.7146528
DO - 10.1109/PERCOM.2015.7146528
M3 - Chapter (peer-reviewed)
SN - 9781479980345
SP - 189
EP - 197
BT - IEEE International Conference on Pervasive Computing and Communications
PB - IEEE
ER -