Increasing Smartphone User Privacy Through Objective-Driven Context Mocking (Complete)

Smartphone apps are already able to determine a great deal about us through passive observation, and as smartphone usage becomes more pervasive and analytical approaches that fuse data from multiple sensors improve, smartphones may reveal fundamental things about us: the strength of our friendships, the health of our lifestyle, and our level of happiness. With the digital portraits smartphones can paint becoming more clear, we believe it is time to give users more control over their smartphone-derived digital identities.

While many projects on smartphone security focus on trying to preserve user privacy, we investigated a different approach. Instead of focusing on privacy, we improved control by using synthetic or "mocked" data to manipulate data-driven analytics as directed by the user. In contrast to privacy, which aims to limit access to data, mocking reduces the percentage of legitimate data by injecting false data to achieve user-defined objectives: to seem more active, more social, or wealthier.

Eventually, through modifications to the Android platform, our approach was able to feed mocked data to unsuspecting apps. The video that follows demonstrates a mocking session of a GPS-based mapping app called Waze. Note that the smartphone is stationary, yet the app believes that the user is walking around our University at Buffalo campus:

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Created 2/11/2016
Updated 2/11/2016
Commit ed24937 // History // View
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