  People use mobile devices ubiquitously for computing, communication, storage,
web browsing, and more. As a result, the information accessed and stored within
mobile devices, such as financial and health information, text messages, and
emails, can often be sensitive. Despite this, people frequently use their
mobile devices in public areas, becoming susceptible to a simple yet effective
attack, shoulder surfing. Shoulder surfing occurs when a person near a mobile
user peeks at the user's mobile device, potentially acquiring passcodes, PINs,
browsing behavior, or other personal information. We propose Eye-Shield, a
solution to prevent shoulder surfers from accessing or stealing sensitive
on-screen information. Eye-Shield is designed to protect all types of on-screen
information in real time, without any serious impediment to users' interactions
with their mobile devices. Eye-Shield generates images that appear readable at
close distances, but appear blurry or pixelated at farther distances and wider
angles. It is capable of protecting on-screen information from shoulder
surfers, operating in real time, and being minimally intrusive to the intended
users. Eye-Shield protects images and text from shoulder surfers by reducing
recognition rates to 24.24% and 15.91%. Our implementations of Eye-Shield, with
frame rates of 24 FPS for Android and 43 FPS for iOS, effectively work on
screen resolutions as high as 1440x3088. Eye-Shield also incurs acceptable
memory usage, CPU utilization, and energy overhead. Finally, our MTurk and
in-person user studies indicate that Eye-Shield protects on-screen information
without a large usability cost for privacy-conscious users.
