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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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Are Consumers Willing to Pay for Security and Privacy of IoT Devices?
Internet of Things (IoT) device manufacturers provide little information to consumers about their security and data handling practices. Therefore, IoT consumers cannot make informed purchase choices around security and privacy. While prior research has found that consumers would likely consider security and privacy when purchasing IoT devices, past work lacks empirical evidence as to whether they would actually pay more to purchase devices with enhanced security and privacy. To fill this gap, we conducted a two-phase incentive compatible online study with 180 Prolific participants. We measured the impact of five security and privacy factors (e.g., access control) on participants’ purchase behaviors when presented individually or together on an IoT label. Participants were willing to pay a significant premium for devices with better security and privacy practices. The biggest price differential we found was for de-identified rather than identifiable cloud storage. Mainly due to its usability challenges, the least valuable improvement for participants was to have multi-factor authentication as opposed to passwords. Based on our findings, we provide recommendations on creating more effective IoT security and privacy labeling programs.
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- Award ID(s):
- 1801472
- PAR ID:
- 10399845
- Date Published:
- Journal Name:
- In Proceedings of the 32nd USENIX Security Symposium
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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