A new technique to detect a drone camera illicitly capturing video has been revealed in a study, ‘Game of Drones – Detecting Captured Target from an Encrypted Video Stream,’ published by Ben-Gurion University of the Negev (BGU) and Weizmann Institute of Science cyber security researchers.
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The study addresses increasing concerns about the proliferation of drone use for personal and business applications and how it is impinging on privacy and safety.
In the new paper, the researchers demonstrate techniques for detecting whether a targeted subject or house is being recorded by a drone camera.
“The beauty of this research is that someone using only a laptop and an object that flickers can detect if someone is using a drone to spy on them,” says Ben Nassi, a Ph.D. student of Prof. Yuval Elovici’s in BGU’s Department of Software and Information Systems Engineering and a researcher at the BGU Cyber Security Research Center. Elovici is the Center’s director as well as the director of Telekom Innovation Labs at BGU. The research team also includes Raz Ben-Netanel, a student in the BGU Department of Communication Systems Engineering. Prof. Adi Shamir from the Weizmann Institute of Science conceived the ‘Game of Drones’ technique.
While it has been possible to detect a drone, now someone can also tell if it is recording a video of your location or something else, the researchers add.
The first demo showed how a privacy invasion against a house can be detected, using smart film placed on a window and entering a few software commands on a laptop to access the encrypted video seen by the drone operator, called the FPV channel. This enabled the researchers to demonstrate how they were able to detect that a neighbor was using a DJI Mavic drone to capture images of his own home and then illicitly stream video of his neighbor’s house, as well.
(The demonstration video is seen above.)
In a second outdoor test, researchers demonstrate how an LED strip attached to a person wearing a white shirt can be used to detect targeted drone activity. When researchers flickered the LED lights on the cyber-shirt, it caused the FPV channel to send an “SOS” by modulating changes in data sent by the flickering lights.
“This research shatters the commonly held belief that using encryption to secure the FPV channel prevents someone from knowing they are being tracked,” Nassi says. “The secret behind our method is to force controlled physical changes to the captured target that influence the bitrate (data) transmitted on the FPV channel.”
This method can be used on any laptop that runs Linux OS and does not require any sophisticated hacking or cryptographic skills.
“Our findings may help thwart privacy invasion attacks that are becoming more common with increasing drone use,” Nassi says. “This could have significant impact for the military and for consumers because a victim can now legally prove that a neighbor was invading their privacy.”
In previous research, Nassi showed how a laser mounted to a DJI Inspire 1 drone can use malware installed on an isolated (air-gapped) network scanner.