Abstract
We studied the fusion of three biometric authentication modalities, namely, swiping gestures, typing patterns and the phone movement patterns observed during typing or swiping. A web browser was customized to collect the data generated from the aforementioned modalities over four to seven days in an unconstrained environment. Several features were extracted by using sliding window mechanism for each modality and analyzed by using information gain, correlation, and symmetric uncertainty. Finally, five features from windows of continuous swipes, thirty features from windows of continuously typed letters, and nine features from corresponding phone movement patterns while swiping/typing were used to build the authentication system. We evaluated the performance of each modality and their fusion over a dataset of 28 users. The feature-level fusion of swiping and the corresponding phone movement patterns achieved an authentication accuracy of 93.33%, whereas, the score-level fusion of typing behaviors and the corresponding phone movement patterns achieved an authentication accuracy of 89.31 %.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781467397339 |
| DOIs | |
| State | Published - Dec 19 2016 |
| Event | 8th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2016 - Niagara Falls, United States Duration: Sep 6 2016 → Sep 9 2016 |
Other
| Other | 8th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2016 |
|---|---|
| Country | United States |
| City | Niagara Falls |
| Period | 9/6/16 → 9/9/16 |
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ASJC Scopus subject areas
- Statistics and Probability
- Biomedical Engineering
- Computer Science Applications
Cite this
Continuous authentication of smartphone users by fusing typing, swiping, and phone movement patterns. / Kumar, Rajesh; Phoha, Vir; Serwadda, Abdul.
2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7791164.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Continuous authentication of smartphone users by fusing typing, swiping, and phone movement patterns
AU - Kumar, Rajesh
AU - Phoha, Vir
AU - Serwadda, Abdul
PY - 2016/12/19
Y1 - 2016/12/19
N2 - We studied the fusion of three biometric authentication modalities, namely, swiping gestures, typing patterns and the phone movement patterns observed during typing or swiping. A web browser was customized to collect the data generated from the aforementioned modalities over four to seven days in an unconstrained environment. Several features were extracted by using sliding window mechanism for each modality and analyzed by using information gain, correlation, and symmetric uncertainty. Finally, five features from windows of continuous swipes, thirty features from windows of continuously typed letters, and nine features from corresponding phone movement patterns while swiping/typing were used to build the authentication system. We evaluated the performance of each modality and their fusion over a dataset of 28 users. The feature-level fusion of swiping and the corresponding phone movement patterns achieved an authentication accuracy of 93.33%, whereas, the score-level fusion of typing behaviors and the corresponding phone movement patterns achieved an authentication accuracy of 89.31 %.
AB - We studied the fusion of three biometric authentication modalities, namely, swiping gestures, typing patterns and the phone movement patterns observed during typing or swiping. A web browser was customized to collect the data generated from the aforementioned modalities over four to seven days in an unconstrained environment. Several features were extracted by using sliding window mechanism for each modality and analyzed by using information gain, correlation, and symmetric uncertainty. Finally, five features from windows of continuous swipes, thirty features from windows of continuously typed letters, and nine features from corresponding phone movement patterns while swiping/typing were used to build the authentication system. We evaluated the performance of each modality and their fusion over a dataset of 28 users. The feature-level fusion of swiping and the corresponding phone movement patterns achieved an authentication accuracy of 93.33%, whereas, the score-level fusion of typing behaviors and the corresponding phone movement patterns achieved an authentication accuracy of 89.31 %.
UR - http://www.scopus.com/inward/record.url?scp=85011265958&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85011265958&partnerID=8YFLogxK
U2 - 10.1109/BTAS.2016.7791164
DO - 10.1109/BTAS.2016.7791164
M3 - Conference contribution
BT - 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -