Citadel Defense AI and machine learning technology to take down nefarious drones

May 28, 2020
As adversaries look for ways to spoof counter unmanned aerial systems (C-UAS), Citadel responds with speed and agility.

SAN DIEGO, Calif., - Citadel Defense has released new software incorporating deepfake neural networks to defend against adversarial spoofing tactics. This capability helps U.S. and allied forces combat growing enemy tactics that attempt to confuse existing and security intelligence equipment as spectrum superiority becomes more important.

Citadel was the first company to use artificial intelligence and machine learning to counter unmanned system threats. The company has now taken a quantum leap forward by using Generative Adversarial Networks in their Titan C-UAS solution.

Christopher Williams, CEO of Citadel Defense explains, “Just like anti-virus programs have methods to detect software exploits, 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, Citadel 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.

As the use of drones and surface-based robotic platforms proliferate on the battlefield, Citadel is rapidly equipping militaries and governments with the most cutting-edge capabilities to stay ahead of the weaponized drone threat.

In the last three months, Citadel has trained over 500 military and law enforcement operators on emerging adversarial threat tactics and Titan technology. Over 100 Titan systems are being updated with the company’s latest software release.

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