Securing Smart Home Iot Applications Via Wireless Traffic Analysis

Abstract

Householders have widely used IoT security systems with the development of smart home applications. Wireless security cameras are integral components of IoT security systems used by many private homes. These cameras commonly employ motion sensors to identify something occurring in their fields of vision before recording and notifying the property owner of the activity. In this thesis, we discover that the motion-sensing action can disclose the camera's location through a novel wireless camera localization technique we call MotionCompass. In short, a user who aims to avoid surveillance can find a hidden camera by creating motion stimuli and sniffing wireless traffic for a response to that stimuli. With the motion trajectories within the motion detection zone, the user can then compute the camera's exact location. We develop an Android app to implement MotionCompass. Our extensive experiments using the developed app and 18 popular wireless security cameras demonstrate that MotionCompass can attain a mean localization error of around 5 cm in less than 140 seconds for cameras with one motion sensor. This localization technique builds upon existing work that detects the existence of hidden cameras to pinpoint their exact location and area of surveillance.