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Mobile computing is the new norm. As people feel increasingly comfortable computing in public places such as coffee shops and transportation hubs, the threat of exposing sensitive information increases. While solutions exist to guard the communication channels used by mobile devices, the visual channel remains, to a significant degree, open. Shoulder surfing is becoming a viable threat in a world where users are frequently surrounded by high-power cameras, and where sensitive information from recorded images can be extracted with modest computing power. In response, this dissertation presents Cashtags: a system to defend against attacks on mobile devices based on visual observations. The system allows users to access sensitive information in public without the fear of visual leaks. This is accomplished by intercepting sensitive data elements before they are displayed on screen, then replacing them with non-sensitive information. In addition, the system provides a means of computing with sensitive data in a non-observable way. All of this is accomplished while maintaining full functionality and legacy compatibility across applications.
Anonymity, Human-computer Interaction, Mobile Systems, Privacy, Security
Date of Defense
April 15, 2015.
Submitted Note
A Dissertation submitted to the Department of Computer Science in partial fulfillment of the Doctor of Philosophy.
Bibliography Note
Includes bibliographical references.
Advisory Committee
An-I Andy Wang, Professor Directing Dissertation; Linda DeBrunner, University Representative; Gary Tyson, Committee Member; Zhi Wang, Committee Member.
Publisher
Florida State University
Identifier
FSU_migr_etd-9412
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