Abstract

The emerging ubiquity of devices with monitoring capabilities has resulted in a growing privacy concerns. This work addresses the challenge of automatically identifying devices that are streaming privacy-intruding information about a user. The work includes a framework for inducing a signal in the physical world and then detecting its digital footprint when devices are monitoring the user. The approach only requires the user to have a device with the ability to enter into network monitor mode. The techniques described work regardless of if the camera uses encryption or is even on the same network as the device. The effectiveness of this approach has been demonstrated through analyzing over 15 hours of network traffic. The technique detected over 90% of the hidden cameras across a variety of physical environments while producing less than 6% false positives within 30 seconds of the camera beginning to stream recordings

• http://www.brentlagesse.net
• https://faculty.washington.edu/lagesse/publications/HiddenSensorDetection.pdf