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Performance Analysis of Motion-Sensor Behavior for User Authentication on Smartphones.
Chao Shen1, Tianwen Yu2, Sheng Yuan3
1School of Electronic and Information Engineering, Xi'an Jiaotong University, 710049 Xi'an, China. cshen@sei.xjtu.edu.cn.
Sensors (Basel, Switzerland)
|March 24, 2016
Summary
Smartphone authentication can be enhanced using motion-sensor data. Analyzing user passcode input via motion sensors offers a viable method for secure authentication, approaching two-factor capabilities.
Area of Science:
- Computer Science
- Human-Computer Interaction
- Cybersecurity
Background:
- Smartphones store sensitive data, increasing the need for robust security.
- Traditional authentication methods face challenges with usability and security.
- Motion-sensor data offers a novel approach to user authentication.
Purpose of the Study:
- To investigate the use of motion-sensor behavior data for smartphone user authentication.
- To evaluate the accuracy and practicality of sensor-based authentication.
- To assess the potential for motion-sensor data in enhancing smartphone security.
Main Methods:
- Collected motion-sensor data during passcode entry from 48 participants.
- Extracted descriptive and intensive features from sensor data.
- Applied one-class learning methods for user authentication.
- Conducted experiments across various scenarios and smartphone types.
Main Results:
- Achieved a false-rejection rate of 6.85% and a false-acceptance rate of 5.01%.
- Demonstrated effectiveness across different passcode lengths, training set sizes, user numbers, and screen sizes.
- Sensor data provides valuable authentication information.
Conclusions:
- Motion-sensor behavior data is a feasible and effective method for smartphone authentication.
- The achieved performance is close to sufficient for two-factor authentication.
- The publicly available dataset facilitates further research in this area.
