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Title: Which Privacy and Security Attributes Most Impact Consumers’ Risk Perception and Willingness to Purchase IoT Devices?
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  more » « less
Award ID(s):
1801472 1564009
NSF-PAR ID:
10316411
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
2021 IEEE Symposium on Security and Privacy (SP)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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