PREVENTING USER AND HARDWARE TRACKING IN MOBILE DEVICES
by
David Robert Stites
B.S., Purdue University, 2007
Thesis directed by Professor Rory Lewis
A thesis submitted to the Graduate Faculty of the University of Colorado at Colorado Springs in partial fulfillment of the requirements for the degree of Master of Science
Department of Computer Science
© Copyright By David Robert Stites 2012 All Rights Reserved
Mobile devices, such as smartphones or PDAs, have become increasingly popular with consumers and often provide essential functionality in their everyday life. Usually these mobile devices contain a great deal of sensitive information such as addresses, contacts, ingoing/outgoing call logs, SMS messages and, on the latest models, a calendar, emails and potentially the user’s current location. A smartphone or mobile device today can be as powerful as a desktop or laptop in some respects and, while the latest models feature a complete OS, for many users these devices are “just phones” so there is an underestimation of the risk connected to mobile device privacy. There is a currently existing privacy problem associated with user and hardware tracking in mobile devices. Users can be tracked without their knowledge and consent and have rich profiles built about them using their hardware interface address regarding their location and preferences. This information can be potentially cross correlated to other existing datasets to build advertising profiles for these users. The mitigation to this problem using a framework to support randomly generated, disposable hardware addresses.
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