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   https://doi.org/https://doi.org/10.1007/s13235-021-00386-z  

   Gradwohl, Ronen; Smorodinsky, Rann (January 2021, Dynamic games and applications)
2. Understand Users’ Privacy Perception and Decision of V2X Communication in Connected Autonomous Vehicles

   Zekun Cai and Aiping Xiong (August 2023, Proceedings of the USENIX conference)
3. Which Privacy and Security Attributes Most Impact Consumers’ Risk Perception and Willingness to Purchase IoT Devices?

   https://doi.org/10.1109/SP40001.2021.00112  

   Emami-Naeini, Pardis; Dheenadhayalan, Janarth; Agarwal, Yuvraj; Cranor, Lorrie Faith (May 2021, 2021 IEEE Symposium on Security and Privacy (SP))

   In prior work, researchers proposed an Internet of Things (IoT) security and privacy label akin to a food nutrition label, based on input from experts. We conducted a survey with 1,371 Mechanical Turk (MTurk) participants to test the effectiveness of each of the privacy and security attribute-value pairs proposed in that prior work along two key dimensions: ability to convey risk to consumers and impact on their willingness to purchase an IoT device. We found that the values intended to communicate increased risk were generally perceived that way by participants. For example, we found that consumers perceived more risk when a label conveyed that data would be sold to third parties than when it would not be sold at all, and that consumers were more willing to purchase devices when they knew that their data would not be retained or shared with others. However, participants’ risk perception did not always align with their willingness to purchase, sometimes due to usability concerns. Based on our findings, we propose actionable recommendations on how to more effectively present privacy and security attributes on an IoT label to better communicate risk to consumers 

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4. Disaster privacy/privacy disaster

   https://doi.org/10.1002/asi.24353  

   Sanfilippo, Madelyn R.; Shvartzshnaider, Yan; Reyes, Irwin; Nissenbaum, Helen; Egelman, Serge (March 2020, Journal of the Association for Information Science and Technology)
5. "I would not install an app with this label": Privacy Label Impact on Risk Perception and Willingness to Install iOS Apps

   Balas, David G; Ali, Mir Masood; Kanich, Chris; Aviv, Adam J (August 2024, USENIX)

   Starting December 2020, all new and updated iOS apps must display app-based privacy labels. As the first large-scale implementation of privacy nutrition labels in a real-world setting, we aim to understand how these labels affect perceptions of app behavior. Replicating the methodology of Emani-Naeini et al. [IEEE S&P '21] in the space of IoT privacy nutrition labels, we conducted an online study in January 2023 on Prolific with n=1,505 participants to investigate the impact of privacy labels on users' risk perception and willingness to install apps. We found that many privacy label attributes raise participants' risk perception and lower their willingness to install an app. For example, when the app privacy label indicates that financial info will be collected and linked to their identities, participants were 15 times more likely to report increased privacy and security risks associated with the app. Likewise, when a label shows that sensitive info will be collected and used for cross-app/website tracking, participants were 304 times more likely to report a decrease in their willingness to install. However, participants had difficulty understanding privacy label jargon such as diagnostics, identifiers, track and linked. We provide recommendations for enhancing privacy label transparency, the importance of label clarity and accuracy, and how labels can impact consumer choice when suitable alternative apps are available. 

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