1. Secure graphical password system for high traffic public areas
Bogdan Hoanca and Kenrick Mock
University of Alaska Anchorage

2. Outline Shoulder surfing as security threat in information systems
Eye tracking based authentication
Error rates of eye tracking hardware
Error-aware eye tracking
Systematic errors
Random errors
Conclusions
March 27, 2006
Hoanca/Mock ETRA 2006

3. Shoulder surfing Stealing authentication information
Critical threat for mobile users or in public places
Safest bet: assume “naked” user under constant surveillance
March 27, 2006
Hoanca/Mock ETRA 2006

4. Defending against shoulder surfing
Screen filters
Challenge-response schemes
Physical key schemes
Biometric schemes
March 27, 2006
Hoanca/Mock ETRA 2006

5. Eye tracking based authentication
Use the eye tracker without on-screen feedback to select on-screen objects
Ideally, transparent for the user
Secure from shoulder surfing
Slower than typing
Still vulnerable to key logger and screen capture programs
March 27, 2006
Hoanca/Mock ETRA 2006

6. Graphical Password Entry via Eye Tracking
March 27, 2006
Hoanca/Mock ETRA 2006

7. Sample authentication log
March 27, 2006
Hoanca/Mock ETRA 2006
Image size 700x482

8. High error rates due to hardware limitations
“Low error” user
Mean D = 12 pixels
“High error” user
Mean D = 30 pixels
Plots of actual gaze location as compared with intended target (red); black is the center of gravity
Distances are in pixels and scale is -40…40 in both X and Y
March 27, 2006
Hoanca/Mock ETRA 2006

9. Error rates of eye tracking hardware
Using the ERICA system from Eye Response Technologies
Error types
Systematic errors
Due to head tilt
Slowly varying with time
Dependent on screen geometry and location
Random errors
Highly user dependent
March 27, 2006
Hoanca/Mock ETRA 2006

10. Handling random errors
Loss of cryptographic complexity depends on how much error is acceptable
Success rate (%, 0…100) vs.
distance in pixels (1…1000, log scale)
March 27, 2006
Hoanca/Mock ETRA 2006

11. Handling systematic errors
Red – raw data
Green -- corrected
Success rate (%, 0…100) vs.
distance in pixels (1…1000, log scale)
one user
25 sessions
“low error”
Average over multiple attempts or over multiple users
Loss of cryptographic complexity – equivalent to one click less
March 27, 2006
Hoanca/Mock ETRA 2006

12. Handling systematic errors (continued)
Success rate (%, 0…100) vs.
distance in pixels (1…1000, log scale)
one user
25 sessions
“high error”
Limited usefulness for high error users
Red – raw data
Green -- corrected
March 27, 2006
Hoanca/Mock ETRA 2006

13. Summary
Eye tracking is a promising technology for authenticating from public places with reduced danger of shoulder surfing
Wide acceptance will require eye tracking technologies that are
More stable and accurate
Ideally, head tracking-capable and calibration-free
Much lower in price
March 27, 2006
Hoanca/Mock ETRA 2006