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As the use of drones and surface-based robotic platforms proliferate on the battlefield, adversaries are looking for ways to spoof counter unmanned aerial systems (C-UAS). A new technology will help combat growing enemy tactics that attempt to confuse existing security intelligence equipment.
Citadel Defense has released new software incorporating deepfake neural networks to protect against adversarial spoofing tactics. Its Titan system prevents group I and II unmanned system threats from entering a protected airspace.
The company was the first to use artificial intelligence and machine learning to counter unmanned system threats, according to businesswire.com. The Generative Adversarial Networks in the Titan C-UAS solution is another step in that direction.
Titan has automated methods that proactively defend against spoofing exploits. Adding new deep learning capabilities to Titan helps blind the drone-equipped enemy and deny them any advantage or safe haven in contested and complex radiofrequency environments.
Using proprietary image generation algorithms, the company has developed discrimination classification models that help determine whether the signal detected is a real drone or a generated signal by the adversary trying to trick existing signal intelligence equipment.