Adversarial Localization against Wireless Cameras

Zhijing Li, Zhujun Xiao, Yanzi Zhu, Irene Pattarachanyakul, Ben Y. Zhao, Haitao Zheng

Abstract: This paper identifies and empirically evaluates the effectiveness of adversarial localization attacks against wireless IoT devices, e.g., wireless security cameras in the home. We use experiments in home and office settings to show that attackers can accurately pinpoint the location of WiFi cameras, using a small amount of stealthy, passive, exterior measurements coupled with unsupervised learning techniques. We also show that current defenses have minimal impact against these attacks, and are also easily circumvented via countermeasures. Thus significant work is needed to develop robust defenses against these attacks.