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With the proliferation of IoT devices, there are growing concerns about being sensed or monitored by these devices unawares, especially in places perceived as private. We explore the design space of IoT locators to help people physically find nearby IoT devices. We first conducted a survey to understand people's willingness, current practices, and challenges in finding IoT devices. Our survey findings motivated us to design and implement low-cost locators (visual, auditory, and contextualized pictures) to help people find nearby devices. Through an iterative design process and two rounds of experiments, we found that these locators greatly reduced people's search time over a baseline of no locators. Many participants found the visual and auditory locators enjoyable. Some participants also appropriated the use of our system for other purposes, e.g., to learn about new IoT devices, instead of for privacy awareness.
Connected devices in the home represent a potentially grave new privacy threat due to their unfettered access to the most personal spaces in people's lives. Prior work has shown that despite concerns about such devices, people often lack sufficient awareness, understanding, or means of taking effective action. To explore the potential for new tools that support such needs directly we developed Aretha, a privacy assistant technology probe that combines a network disaggregator, personal tutor, and firewall, to empower end-users with both the knowledge and mechanisms to control disclosures from their homes. We deployed Aretha in three households over six weeks, with the aim of understanding how this combination of capabilities might enable users to gain awareness of data disclosures by their devices, form educated privacy preferences, and to block unwanted data flows. The probe, with its novel affordances—and its limitations—prompted users to co-adapt, finding new control mechanisms and suggesting new approaches to address the challenge of regaining privacy in the connected home.
Personal data collected by fitness trackers can leave users open to security and privacy threats, often without their knowledge. Using an online survey with 212 fitness tracker users, we asked questions to understand participants' knowledge, attitudes and behaviours related to security and privacy, associated with the use of their fitness trackers. We found that users do little to protect their data. While they seem confident about the type of data being collected, they are unsure about how it is being used. Understandably, users are more comfortable sharing their data with friends and work colleagues. We also found that users differentiate between the types of data they are willing to share, suggesting a need for improved sharing preferences. When considering scenarios describing data uses with security and privacy implications, participants recognized that many scenarios were plausible but frequently felt that the scenarios were unlikely to occur. Overall, our findings lead us to believe that fitness tracker users require a greater awareness of the collection, ownership, storage, and sharing practices related to the tracking of their data.
Internet of Things (IoT) devices create new ways through which personal data is collected and processed by service providers. Frequently, end users have little awareness of, and even less control over, these devices' data collection. IoT Personalized Privacy Assistants (PPAs) can help overcome this issue by helping users discover and, when available, control the data collection practices of nearby IoT resources. We use semi-structured interviews with 17 participants to explore user perceptions of three increasingly more autonomous potential implementations of PPAs, identifying benefits and issues associated with each implementation. We find that participants weigh the desire for control against the fear of cognitive overload. We recommend solutions that address users' differing automation preferences and reduce notification overload. We discuss open issues related to opting out from public data collections, automated consent, the phenomenon of user resignation, and designing PPAs with at-risk communities in mind.
"Always-on" smart speakers have raised privacy and security concerns, to address which vendors have introduced customizable privacy settings. But, does the act of customizing one's privacy preferences have any effects on user experience and trust? To address this question, we developed an app for Amazon Alexa and conducted a user study (N = 90). Our data show that the affordance to customize privacy settings enhances trust and usability for regular users, while it has adverse effects on power users. In addition, only enabling privacy-setting customization without allowing content customization negatively affects trust among users with higher privacy concerns. When they can customize both content and privacy settings, user trust is highest. That is, while privacy customization may cause reactance among power users, allowing privacy-concerned individuals to simultaneously customize content can help to alleviate the resultant negative effect on trust. These findings have implications for designing more privacy-sensitive and trustworthy smart speakers.