In the world of consumer privacy, including the Internet of Things (IoT), mobile data, and advertising technologies (“Ad Tech”), it can often be difficult to measure real-world impact and conceptualize individual harms and benefits. Fortunately, academic researchers are increasingly focusing on these issues, leading to impressive scholarship from institutions such as the Princeton Center for Information Technology Policy (CITP), Carnegie Mellon University School of Computer Science, UC Berkeley School of Information, and many others, including non-profits and think tanks.
At events like the Privacy Law Scholars Conference, recently held in Washington, DC (PLSC 2018, May 30-31), privacy-minded scholars from around the world and across disciplines meet to share their research and new ideas each year. Many other conferences sponsor and call for technical privacy research, such as the Privacy Enhancing Technologies Symposium (PETS), which recently announced its accepted papers for 2018. Empirical studies from privacy researchers such as these are an invaluable part of having reasonable and concrete policy debates.
In this study, the authors set up six common IoT devices, and observed network traffic in order to assess privacy and security risks of home devices, as well as study their effects on bandwidth and power consumption. Readers interested in this topic should also check out an oft-cited paper presented at FTC’s 2016 PrivacyCon: A Smart Home is No Castle: Privacy Vulnerabilities of Encrypted IoT Traffic, by Noah Apthorpe, Dillon Reisman, and Nick Feamster (Princeton University).
Based on workshops and interviews with 40 experts, practitioners and scholars (including from Future of Privacy Forum), this report explores the privacy challenges of connected devices and the emerging strategies to address them, including issues of transparency, consent, identifiability, emotional and bodily privacy, and the destabilization of boundaries. UC Berkeley’s Center for Long-Term Cybersecurity published a short white paper version of the research.
In this paper, similar to the one above, the authors demonstrate a 90%+ success rate for re-identifying users on the basis of their mobile gestures. As we learn more about the use of mobile sensors for inferring behavior (for example, whether a user is intoxicated), fingerprinting of sensor data from mobile devices may become one of the next major considerations for consumer privacy.
Researchers from UC Berkeley and International Computer Science Institute, and University of British Columbia, have demonstrated a way to efficiently analyze network traffic for mobile privacy implications in 80,000 Android apps in the Google Play store.
Why Am I Seeing This Ad? The Effect of Ad Transparency on Ad Effectiveness by Tami Kim, Darden School of Business; Kate Barasz, IESE Business School; and Leslie K. John, Negotiations, Organizations, and Markets Unit at Harvard Business School.
Predicted outcomes for ad effectiveness, according to Tami Kim, et al, based on whether the consumer trusts the platform and finds the underlying data flows acceptable. Source: Figure 1, p. 15 of “Why Am I Seeing This Ad? The Effect of Ad Transparency on Ad Effectiveness” by Tami Kim et al.
In this paper, Stacia Garlach and Professor Daniel D. Suthers investigate a small sample of smartphone users, and explore whether and how they notice, understand, and use the “AdChoices” icon in typical mobile advertisements.
Several papers listed above are accepted papers for the 2018 Privacy Enhancing Technologies Symposium (PETS) (July 24-27, 2018).