Hello! My name is Parth Thakkar and I'm am a master's student in Human Centered Computing
at the University of Maryland Baltimore County. Today I will be presenting on
behalf of my co-authors or paper which relates to privacy awareness mechanisms in smart homes.
Smart homes have been increasingly prevalent in recent years due to their great efficiency
and convenience the IoT devices connected in a smart home are equipped with various sensors
which possess the ability to collect massive amount of data of users and their surrounding
environment which pose privacy risk to the users. However, general users have very limited ways to
learn about these data practices thus effective privacy awareness mechanisms to increase both
users and bystanders awareness of data practices are in desperate need. Broadly speaking there are
two types of stakeholders involved in smart home users and bystanders. In our study,
we define smart home users as those who own smart home devices and define smart home bystanders
as those who do not own smart home devices but may be subject to the data collection by smart
home devices. Previous studies indicate that users are typically concerned about
their personal data being collected, shared, analyzed as well as their home being hacked.
On other hand bystanders are generally unaware of the data collection around them putting the
privacy at risk. The research questions identified for our study are as follows: What factors
influence users and bystander preferences for receiving privacy notifications in smart homes?
Which modality do users and bystanders prefer to receive privacy notifications in smart homes?
And lastly, How do the preferences differ between users and bystanders in smart homes.
To find answers to our research questions we conducted a survey study focused on understanding
participants general preferences of receiving privacy notice in smart homes as well as the
perceptions of four privacy awareness mechanisms which include an Interactive Privacy
Dashboard, a Smartphone App, an Ambient Light and a Smart Speaker. We recruited our participants
from prolific which is an online participant recruitment platform. Summarizing our participant
demographics both users and bystanders represent a diverse background in terms of their age, gender,
education level and work status. Our sample also represents a good mix of users and bystanders in
terms of their prior experiences with smart home devices as well as device ownership. Both users
and bystanders have relatively higher levels of privacy concerns towards smart home devices
our survey was inclusive of both qualitative and quantitative questions for qualitative
data we conducted thematic analysis to identify various themes including the pros and cons of each
awareness mechanism as well as why participants prefer certain mechanisms in different scenarios.
In addition, we also analyze the quantitative data to understand participants perceptions
towards different mechanisms including perceived effectiveness, perceived ease to use
and willingness to use regarding each awareness mechanism. Talking about the awareness mechanisms,
the Privacy Dashboard is a dashboard that includes details of data practices of surrounding smart
home devices. For Privacy Dashboard the positive themes identified include the dashboard being able
to provide details as a centralized source of information and reduce dependence on its users,
while negative themes which emerged include responses like lack of control violating social
norms and required digital literacy to operate the Data Dashboard. Next, we have the Mobility
App which is a data protector application on your phone which is designed to provide details of data
usage status of surrounding smart devices. The positives identified for Mobility App include the
property of being accessible from users private devices and also its ability to provide detailed
information and overcome social awkwardness. On the negative side participants thought that the
Mobility App might have security concerns since bystanders would need to connect to the user's
home network and scan all connected devices at the user's home also leading to invasion of users
privacy. Moving on to the next mechanism Ambient Lighting is a smart bulb-based product that is
dedicated to provide users with notifications regarding the data collection in smart homes by
changing its color. Themes like easy to understand and unobtrusive way to deliver notifications came
forward as positives while the negatives included themes like not being able to provide enough
information requiring much effort and being a psychological burden for the users. This is
because participants mentioned that red color can be very intimidating and could potentially cause
anxiety. Lastly, the Privacy Speaker is an audio IoT network traffic notification system for smart
homes. Participant responses indicated that the privacy speaker to be effortless and being able to
reduce social confrontations when they wanted to be aware of the data collection in other people's
homes as one of the positive themes but also having negatives for the awareness mechanism
being annoying less informative and cause anxiety to users as a result of repeatedly hearing a voice
message about their data being collected. In our survey, we also presented four scenarios
namely Bio-metric Security, Visiting a Friend, Work From Home and Health Data Tracking these
scenarios were followed by a set of questions to understand participants mechanism preferences
in each. Our results indicate that Mobility App is consistently recognized as the most preferred
mechanism across all four scenarios. The Data Dashboard is the second most preferred mechanism
by the participants followed by the Ambient Lighting and the Privacy Speaker respectively
we also noticed that some mechanisms are better perceived in certain scenarios compared to others.
For example, the Ambient Light is more welcomed in the Work From Home scenario
mostly because it can raise people's awareness of surrounding data practices in an unobtrusive
way. We also received a number of responses which indicated the preference as none. The most common
reason being that the participants did not care about the data being collected in smart homes.
Here, I summarized the key takeaways from our study. Key takeaways from our studie include a
number of similarities and differences between the users and bystanders. Similarities include
that both users and bystanders prefer to have detailed information about their data practices
surrounding smart home devices. Also, all participants prefer privacy notices which
provide easy access and offer some sort of control to make privacy choices. We also observed a number
of differences between users and bystanders but the one that stood out was that users tend to
prioritize device utility over privacy protection while bystanders tend to consider social factors
such as social relationships and power dynamics. Based on our findings, we summarize the
following key design implications for future privacy awareness mechanisms in smart homes.
The design implications include Easy access, Unobtrusive Modality to deliver privacy notice,
Privacy Notice at Smart Home Level to provide users with a centralized place to know about their
data practices and lastly Privacy Choices Along With Privacy Notice particularly for bystanders
to protect their privacy. This brings us to the end of our presentation if you would like
to know more about our research please refer to our paper. Thank you so much for your attention!