New research on mobile privacy receives SOUPS 2016 Privacy Award
From left to right: Sunny Consolvo (Google, SOUPS 2016 Program Co-Chair), Florian Schaub, Norman Sadeh (co-author, CMU Professor), Bin Liu (first author, CMU), Yuvraj Agarwal (co-author, CMU Assistant Professor), Matthew Smith (University of Bonn, SOUPS 2016 Program Co-Chair)
UMSI incoming assistant professor Florian Schaub was recently awarded the Symposium on Usable Privacy and Security (SOUPS) 2016 Privacy Award for a paper he co-authored, titled “Follow My Recommendations: A Personalized Privacy Assistant for Mobile App Permissions.”
Schaub, who is also a postdoctoral fellow in the School of Computer Science at Carnegie Mellon University, received the award at this year’s SOUPS conference, held June 22-24 in Denver, CO.
The award is sponsored by the International Association of Privacy Professionals (IAPP) and recognizes the best privacy research paper presented at SOUPS each year.
In this paper, the authors revealed that a personalized privacy assistant (PPA) may help mobile users manage privacy settings by predicting their decisions. The study found that 78.7% of recommendations made by the PPA were adopted by users.
Previous research has found that users are often unaware of, or uncomfortable with, many of their privacy settings. Research in the past has also suggested that it’s possible to predict many of the privacy settings a user would want by asking only a small set of questions.
The authors of this study set out to do just that. In addition to developing a PPA, the authors found that users changed only 1.5% of the settings previously adopted based on the PPA’s recommendations.
“Privacy recommendations introduce a degree of automation to privacy configuration,” the researchers noted in the paper. “Automation can potentially impact technology acceptance. Our results indicate that we have achieved a good balance, given that participants reviewed and edited recommendations while reporting high levels of comfort and usability…While our results and insights pertain primarily to mobile interaction, we expect that personalized privacy assistant approaches can also be applied to support privacy decision making in other domains where privacy configuration or awareness is an issue.”
"Follow My Recommendations: A Personalized Privacy Assistant for Mobile App Permissions" Bin Liu, Mads Schaarup Andersen, Florian Schaub, Hazim Almuhimedi, Shikun Zhang, Norman Sadeh, Alessandro Acquisti. and Yuvraj Agarwal.
The full article can be found here: