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End-User Regression Testing for Privacy

Sheth, Swapneel Kalpesh; Kaiser, Gail E.

Privacy in social computing systems has become a major concern. End-users of such systems find it increasingly hard to understand complex privacy settings. As software evolves over time, this might introduce bugs that breach users' privacy. Further, there might be system-wide policy changes that could change users' settings to be more or less private than before. We present a novel technique that can be used by end-users for detecting changes in privacy, i.e., regression testing for privacy. Using a social approach for detecting privacy bugs, we present two prototype tools. Our evaluation shows the feasibility and utility of our approach for detecting privacy bugs. We highlight two interesting case studies on the bugs that were discovered using our tools. To the best of our knowledge, this is the first technique that leverages regression testing for detecting privacy bugs from an end-user perspective.

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Publisher
Department of Computer Science, Columbia University
Publication Origin
New York
Series
Columbia University Computer Science Technical Reports, CUCS-015-12
Academic Units
Computer Science
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