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The CO-oPS ("Community Oversight for Privacy and Security") app allows trusted community members to review one another’s apps installed and permissions granted to those apps. Community members can provide feedback to one another regarding their privacy behaviors. Users are also allowed to hide some of their mobile apps that they do not like others to see, ensuring their personal privacy. 

We developed “MiSu” an Android and iOS app that allows smart home homeowners to share their devices (e.g., Ring doorbell, security alarm, smart door lock, smart light bulb) with people outside of their home to control what, when, and how they can engage with the smart devices. MiSu provides options for fine-grain access control, the ability for guests to control smart homes using their own device and login, and provides homeowners real-time logs where they can view all actions taken by guests invited to interact with their smart homes. 

Location sharing is a particularly sensitive type of online information disclosure. To explain this behavior, we compared the effectiveness of using self-report measures drawn from the literature, behavioral data collected from mobile phones, and a new type of measure that represents a hybrid of self-report and behavioral data to contextualize users’ attitudes toward their past location sharing behaviors. This new measure was based on a reflective learning paradigm, where one reflects on past behavior to inform future behavior. Based on a study of Android smartphone users (N=114), we found that the construct ‘FYI About Myself’ and our new reflective measure of one’s comfort with sharing location with apps on the smartphone were the best predictors of location sharing behavior. Surprisingly, Behavioral Intention, a commonly used proxy for actual behavior, was not a significant predictor. These results have important implications for privacy research and designing systems to meet users’ location sharing privacy needs. 

People often rely on their friends, family, and other loved ones to help them make decisions about digital privacy and security. However, these social processes are rarely supported by technology. To address this gap, we developed an Android-based mobile application ("app") prototype which helps individuals collaborate with people they know to make informed decisions about their app privacy permissions. To evaluate our design, we conducted an interview study with 10 college students while they interacted with our prototype. Overall, participants responded positively to the novel idea of using social collaboration as a means for making better privacy decisions. Yet, we also found that users are less inclined to help others and may be only willing to partake in conversations that directly affect themselves. We discuss the potential for embedding social processes in the design of systems that support privacy decision-making, as well as some of the challenges of this approach.