Israeli researchers can now track and pinpoint malicious or terrorist drone operators flying in protected air space
The fear of an explosive-laden drone targeting cities anywhere in the world is real. The accompanying panic and chaos could bring any country to a standstill. The fear is trebled such unidentified drones are detected flying near civilian airports endangering flights and passengers. This happened In 2018 when unidentified drones were noticed at the Gatwick Aiport. The fear and chaos caused the authorities to close down the airport for 33 hours between December 19 and 21. And as of today, that particular drone was never identified despite the Gatwick authorities offering a $70,000 reward for such information.
The fear is real and that is why a team of researchers from Israel’s Ben Gurion University took it upon themselves to build a tool that could identify the operators of such malicious or terrorist drones. The team of researchers includes Eliyahu Mashhadi, Yossi Oren, and is led by Dr. Gera Weiss from BGU’s Department of Computer Science,
The BGU researchers used Microsoft’s AirSim to conduct their research and using neutral networking they could predict the location of the drone operator using only flight paths — even when in motion. AirSim is an open-source, cross-platform simulator for drones.
BGU researchers preferred neutral networking instead of RF techniques because of the sheer number of wireless signals in any area at any particular time. “Currently, drone operators are located using RF techniques and require sensors around the flight area which can then be triangulated,” said researcher Eliyahu Mashhadi. “This is challenging due to the amount of other Wi-Fi, Bluetooth, and IoT signals in the air that obstruct drone signals.”
BGU researchers were able to achieve 78% accuracy using their neutral networking method to zoom in on the rogue drone operator. BGU researchers haven’t yet tested their research in a real-world scenario and intend to do it soon. If their research works out as they intend, it could save future terror attacks or panic attacks by pinpointing the drone operator before any harm could be done.
Their research was presented during the Fourth International Symposium on Cyber Security, Cryptography, and Machine Learning (CSCML 2020) held on July 3.