Summary
Smart home devices are vulnerable to passive inference attacks based on network traffic, even in the presence of encryption. In this paper, we present PingPong, a tool that can automatically extract packet-level signatures for device events (e.g., light bulb turning ON/OFF) from network traffic. We evaluated PingPong on popular smart home devices ranging from smart plugs and thermostats to cameras, voice-activated devices, and smart TVs. We were able to: (1) automatically extract previously unknown signatures that consist of simple sequences of packet lengths and directions; (2) use those signatures to detect the devices or specific events with an average recall of more than 97%; (3) show that the signatures are unique among hundreds of millions of packets of real world network traffic; (4) show that our methodology is also applicable to publicly available datasets; and (5) demonstrate its robustness in different settings: events triggered by local and remote smartphones, as well as by home-automation systems.
Papers
- R. Trimananda, J. Varmarken, A. Markopoulou, B. Demsky, “Packet-Level Signatures for Smart Home Devices,” in Proceedings of the 2020 Network and Distributed System Security Symposium (NDSS). February 2020, San Diego, CA.
- R. Trimananda, J. Varmarken, A. Markopoulou, and B. Demsky. Ping-pong: Packet-level signatures for smart home device events. http://arxiv.org/abs/1907.11797.
Team
- Rahmadi Trimananda (UC Irvine, Programming Languages Research Group)
- Janus Varmarken (UC Irvine, Networking Group)
- Athina Markopoulou (UC Irvine, Networking Group)
- Brian Demsky (UC Irvine, Programming Languages Research Group)
Software and Dataset
- Software: please refer to the PingPong project page at the Programming Languages Research Group’s website to access the PingPong software.
- Dataset: please refer to this page to request access to the PingPong dataset.
Contact
If you have any questions about the paper, software, or dataset, please send an email directly to the main author.