Et Tu Alexa? When Commodity WiFi Devices Turn into Adversarial Motion Sensors
Yanzi Zhu
Zhujun Xiao
Yuxin Chen
Zhijing Li
Max Liu
Ben Y. Zhao
Haitao Zheng
The 27th Network & Distributed System Security Symposium (NDSS 2020)
[Full Text in PDF Format, 685KB]
Paper Abstract
Our work demonstrates a new set of silent reconnaissance attacks, which leverages the presence of
commodity WiFi devices to track users inside private homes and offices, without compromising any WiFi
network, data packets, or devices. We show that just by sniffing existing WiFi signals, an adversary
can accurately detect and track movements of users inside a building. This is made possible by our
new signal model that links together human motion near WiFi transmitters and variance of multipath
signal propagation seen by the attacker sniffer outside of the property. The resulting attacks are
cheap, highly effective, and yet difficult to detect. We implement the attack using a single commodity
smartphone, deploy it in 11 real-world offices and residential apartments, and show it is
highly effective. Finally, we evaluate potential defenses, and propose a practical and effective
defense based on AP signal obfuscation.