Discovering Smart Home Internet of Things Privacy Norms Using Contextual Integrity

Abstract

The proliferation of Internet of Things (IoT) devices for consumer "smart" homes raises concerns about user privacy. We present a survey method based on the Contextual Integrity (CI) privacy framework that can quickly and efficiently discover privacy norms at scale. We apply the method to discover privacy norms in the smart home context, surveying 1,731 American adults on Amazon Mechanical Turk. For $2,800 and in less than six hours, we measured the acceptability of 3,840 information flows representing a combinatorial space of smart home devices sending consumer information to first and third-party recipients under various conditions. Our results provide actionable recommendations for IoT device manufacturers, including design best practices and instructions for adopting our method for further research.

23 pages, 5 figures, 3 tables

References in corpus (2)

• The Queen's Guard: A Secure Enforcement of Fine-grained Access Control In Distributed Data Analytics Platforms
• Implicit Contextual Integrity in Online Social Networks

Cited by in corpus (9)

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• Informing the Design of Privacy-Empowering Tools for the Connected Home
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• Occupant Privacy Perception, Awareness, and Preferences in Smart Office Environments
• A Room With an Overview: Towards Meaningful Transparency for the Consumer Internet of Things
• Stop the Spread: A Contextual Integrity Perspective on the Appropriateness of COVID-19 Vaccination Certificates
• Interactive Restriction of a Mobile Robot's Workspace in a Smart Home Environment
• Exploring Smart Commercial Building Occupants' Perceptions and Notification Preferences of Internet of Things Data Collection in the United States
• Evaluating the Contextual Integrity of False Positives in Algorithmic Travel Surveillance