Biometric System Design for Handheld Devices

1. Team 4 Naif Alotaibi, Rich Barilla, Francisco Betances, Aditya Chohan, Alexandra Garcia, Alexander Gazarov, Mantie Reid, and Vinnie Monaco Biometric System Design for Handheld Devices

2. Outline • Introduction • Related Work • Background • Methodology • Data Collection

3. Introduction

4. Related Work • Researchers at University of Hong Kong • Single-Touch, Multi-Touch, Drag • Neural network, error rate of 7.8% • 2012 ACM SIGCHI Conference on Human Factors in Computing Systems • 90% accuracy (single gestures) • Improvement using multiple gestures (sequence)

5. Researchers at the University of Houston • Graphic Touch Gesture Feature (GTGF) • Flick up/down, flick right/left, zoom in/out • Converting touch traces to images • Low Equal Error Rate of 2.62% • Mobile device picking up motion • Trajectory and angle • Error rate of 6.13% • Accuracy declines with user movement

6. Background • Touchscreen • X and Y coordinates of the touch (position) • Pressure of the touch • Size of the contact area • State change (Ex. Up, Down, etc) • Multi-touch screens report multiple movement traces at the same timeusing pointers.

7. Motion sensors: measure acceleration and rotational forces. • Position sensors: used for capturing data about the physical position of the device • Useful sensors for developing our system: • Accelerometer: measure the acceleration applied to the device. • Gyroscope: measures the rotation around the device's axis. • Orientation: measure the position relative to the earth's frame of reference

8. Raw data capture

9. System architecture Main activity (with WebView) Settings activity Biometric event Data file Event buffer SQLite database Network

10. Data Collection

11. Data Collection

12. Results • 98% accuracy within single session • 25% with one session as test and the other as training data

13. Thank You!