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.

View More Papers

OmegaLog: High-Fidelity Attack Investigation via Transparent Multi-layer Log Analysis

Wajih Ul Hassan (University of Illinois Urbana-Champaign), Mohammad A. Noureddine (University of Illinois Urbana-Champaign), Pubali Datta (University of Illinois Urbana-Champaign),...

Read More

Metal: A Metadata-Hiding File-Sharing System

Weikeng Chen (UC Berkeley), Raluca Ada Popa (UC Berkeley)

Read More

Proof of Storage-Time: Efficiently Checking Continuous Data Availability

Giuseppe Ateniese (Stevens Institute of Technology), Long Chen (New Jersey Institute of Technology), Mohammard Etemad (Stevens Institute of Technology), Qiang...

Read More