Text Input Biometric System Design for Handheld Devices

Naif Alotaibi, Emmanuel Pascal Bruno, Michael Coakley, Alexander Gazarov, Vinnie Monaco, Stephen Winard, Filip Witkowski, Alecia Copeland, Peter Nebauer, Christopher Keene, and Joshua Williams

Security of handheld devices• Handheld devices play a major role in our personal and business activities.

• Securing data on the devices is critical• Currently, front-line authentication

measures are used (ex. Passwords)

Keystroke biometric authentication• Identifying users based on typing patterns• Implicit authentication with minimal user

involvement. • The keystroke biometric system at Pace

University is an effective authentication measure

• Implementing and investigate the viability of PKBS on handheld devices

Virtual Keyboards - iOS

• 2007 – the first iPhone• Almost the same keyboard• Special characters• Autocomplete and dictionary

Android keyboards - types

• 2009 – first virtual keyboards in Android 1.5 Cupcake

• Dictionary and Autocomplete• Special characters• Swype

OS Choice: Android

Raw data capture

Typical data

The key code of the touched key

Key press time

Key release time

Touch screen data

Exact touch coordinates in pixels

Finger pressure on the screen

Size and shape of the touched area

Configuration-based data

Current keyboard layout (QWERTY or one of the symbol

layouts)

Current screen orientation

Sensor-based data

Current accelerometer

values indicating the position of the

device

The change of the accelerometer

values since the last measured value

System architecture

BioKeyboard (IME service)

Biometric event

Event buffer SQLite database

Data file

Network

Settings activity

Data CollectedData Type DescriptionAction press or release

Entity code of pressed key

Keyboard Type QWERTY, or symbol layouts

Orientation portrait or landscape

Time timestamp of the event

Coordinates of the touch position

Pressure of the touch

Touch major/minor Tool major/minor

size of the clicked key

Screen data pixel density (dots per inch) & width and height (pixels)

Sensor-based data rotation (X, Y and Z) and acceleration (X, Y and Z)

Session data session ID, session time and user name.

Experimental Results

Conclusions• implemented a software keyboard system to

capture biometric events

• System allows us to run experiments, collect data, and extract features to authenticate users.

Future Work• Developing the feature vector.

• System enhancements: – Capturing gesture/Swype input.– Track spelling suggestions.

Thank You