IoT Inspector: Crowdsourcing Labeled Network Traffic from Smart Home Devices at Scale
Danny Yuxing Huang, Noah Apthorpe, Gunes Acar, Frank Li, Nick Feamster

TL;DR
This paper introduces IoT Inspector, a tool for crowdsourcing labeled network traffic data from smart home devices in real-world settings, enabling large-scale empirical research on security, privacy, and other areas.
Contribution
We developed and released IoT Inspector, an open-source tool that collects and labels network traffic from thousands of smart home devices across many vendors and categories.
Findings
Many devices use outdated TLS versions and weak ciphers.
Discovered 350+ third-party advertiser and tracking domains on smart TVs.
Collected data from 44,956 devices across 13 categories and 53 vendors.
Abstract
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…
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Taxonomy
TopicsInternet Traffic Analysis and Secure E-voting · Privacy, Security, and Data Protection · Advanced Malware Detection Techniques
