Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features
| Autor: | Debayan Deb, Anil K. Jain, Arun Ross, K. Venkatesh Prasad, Kwaku O. Prakah-Asante |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Password 021110 strategic defence & security studies Authentication Network architecture 021103 operations research Biometrics business.industry Computer science Computer Vision and Pattern Recognition (cs.CV) Image and Video Processing (eess.IV) Fingerprint (computing) Computer Science - Computer Vision and Pattern Recognition 0211 other engineering and technologies 02 engineering and technology Electrical Engineering and Systems Science - Image and Video Processing Accelerometer Keystroke dynamics Human–computer interaction FOS: Electrical engineering electronic engineering information engineering Global Positioning System business |
| Zdroj: | ICB |
| DOI: | 10.1109/icb45273.2019.8987433 |
| Popis: | Prevailing user authentication schemes on smartphones rely on explicit user interaction, where a user types in a passcode or presents a biometric cue such as face, fingerprint, or iris. In addition to being cumbersome and obtrusive to the users, such authentication mechanisms pose security and privacy concerns. Passive authentication systems can tackle these challenges by frequently and unobtrusively monitoring the user's interaction with the device. In this paper, we propose a Siamese Long Short-Term Memory network architecture for passive authentication, where users can be verified without requiring any explicit authentication step. We acquired a dataset comprising of measurements from 30 smartphone sensor modalities for 37 users. We evaluate our approach on 8 dominant modalities, namely, keystroke dynamics, GPS location, accelerometer, gyroscope, magnetometer, linear accelerometer, gravity, and rotation sensors. Experimental results find that, within 3 seconds, a genuine user can be correctly verified 97.15% of the time at a false accept rate of 0.1%. |
| Databáze: | OpenAIRE |
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