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

Outline Introduction Related Work Background Methodology Data Collection

Introduction Mobile devices become pervasive Security issues become more important Simple pin or pattern is the only defense There is a need for constant authentication

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)

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

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 time using pointers.

–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 Sensors PositionMotionEnvironment

Raw data capture Device configuration Sensor-based data Touch screen data Pointer coordinates Touch action (down, move, or up) Finger pressure on the screen Size and shape of the touched area Acceleromete r Gravity Rotation System version Device orientation Screen size Screen density

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

Data Collection

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

Thank You!