“You offer privacy like you offer tea”: Investigating Mechanisms for Improving Guest Privacy in IoT-Equipped Households

Abstract

IoT devices are becoming more common and prevalent in private households. Since guests can be present in IoT-equipped households, IoT devices can pose considerable privacy risks to them. In this paper, we present an in-depth evaluation of privacy protection for guests considering the perspectives of hosts and guests. First, we interviewed 21 IoT device owners about four classes of mechanisms obtained from the literature and social aspects. Second, we conducted an online survey (N=264) that investigates the perspective of guests in IoT-equipped households. From our results, we learn that protection mechanisms should not introduce privacy threats and require low resources. Further, hosts should keep control over their devices and the aesthetics of their living spaces. Guests, however, value feedback about the status of privacy protection which can interfere with aesthetics. Privacy protection should rather foster collaboration and not impact the visit of the guest too severely. We use our results to identify a design space for guest privacy protection in IoT-equipped households.

Current topics of interdisciplinary cooperation between engineering and human sciences

“…2017 a, b) Making informed decisions regarding the handling of their private data (Marky et al. 2022 ; Gerber et al. 2021 ; Stöver et al.…”

“…We found that, e.g., guests value feedback about the status of their privacy protection, while IoT device owners fear that such feedback could compromise the aesthetics of their living spaces (Marky et al. 2022 ). We further proposed an interface-based prototype for controlling IoT-equipped households using local information processing, thus protecting the IoT owner from surveillance and hacking attacks (Gerber et al.…”

Privacy-Enhancing Technology and Everyday Augmented Reality

“…It should be noted that many of these points are shared with other smart technologies and pervasive sensing. For example, IoT [87], mobile device sensing [31] and other wearable sensing [118] all have the potential to expose similar data risks. However, everyday AR also poses additional concerns in how this data is actively used/presented in relation to the bystander, such as augmenting bystanders to reveal sensed insights in real-time to the AR user.…”