  The proliferation of smart home devices has created new opportunities for
empirical research in ubiquitous computing, ranging from security and privacy
to personal health. Yet, data from smart home deployments are hard to come by,
and existing empirical studies of smart home devices typically involve only a
small number of devices in lab settings. To contribute to data-driven smart
home research, we crowdsource the largest known dataset of labeled network
traffic from smart home devices from within real-world home networks. To do so,
we developed and released IoT Inspector, an open-source tool that allows users
to observe the traffic from smart home devices on their own home networks.
Since April 2019, 4,322 users have installed IoT Inspector, allowing us to
collect labeled network traffic from 44,956 smart home devices across 13
categories and 53 vendors. We demonstrate how this data enables new research
into smart homes through two case studies focused on security and privacy.
First, we find that many device vendors use outdated TLS versions and advertise
weak ciphers. Second, we discover about 350 distinct third-party advertiser and
tracking domains on smart TVs. We also highlight other research areas, such as
network management and healthcare, that can take advantage of IoT Inspector's
dataset. To facilitate future reproducible research in smart homes, we will
release the IoT Inspector data to the public.
