Unmanned aerial vehicle with immunity to hijacking, jamming, and spoofing attacks

An unmanned aerial vehicle (UAV) comprising:

• a flight package;
• a UAV navigation system;
• a UAV image-acquisition device;
• a UAV communications array including a plurality of agile transceivers;
• a computer memory including a plurality of pre-stored waypoints and flight images of a pre programmed flight path;
• and
• a Generative AI (GenAI) drone inspection network including neural compute engines with Generative Adversarial Networks (GANs) and/or Variational Autoencoders (VAEs),
• the neural compute engine including a processor and instructions, stored in the computer memory and executable by the processor, for using real time data received from one or more of the UAV image-acquisition device, the UAV communications array, or the UAV navigation system as input to the GenAI Network for:
• identifying and classifying (a) that an attack on the UAV is occurring, (b) the characteristics and type of attack, and (c) if the attack is new and uncharacterized,
• where the neural compute engine is configured to:
• send attack data to a HAPS or cloud based neural compute engine if the attack is classified as uncharacterized,
• request updated GAN generator and discriminator weight and configuration files, and/or updated VAE encoder-decoder model and architecture files identifying the characteristics and type of attack. And
• receive updated GAN and/or VAE configuration files with classifications for the type of attack, and mitigation instructions in real time.

A method for a UAV including a flight package, a UAV navigation system, a UAV image-acquisition device, a UAV communications array including a plurality of agile transceivers, a computer memory including a plurality of pre-stored waypoints and flight images of a pre programmed flight path, a Generative AI [GenAI] drone inspection network including neural compute engines with Generative Adversarial Networks [GANs] and/or Variational Autoencoders [VAEs], the neural compute engine including a processor and instructions, stored in the computer memory and executable by the processor, the method comprising:

• using, by the neural compute engine, real time data received from one or more of the UAV image-acquisition device, the UAV communications array or the UAV navigation system as input to the GenAI Network for;
• identifying and classifying, using the GenAI Network, (a) that an attack on the UAV is occurring, (b) characteristics and type of attack, and (c) if the attack is new and uncharacterized
• sending, using the neural compute engine, attack data to a HAPS or cloud based neural compute engine if the attack is classified as uncharacterized,
• requesting, using the neural compute engine, updated GAN generator and discriminator weight and configuration files and/or VAE encoder-decoder model and architecture files identifying the characteristics and type of attack, and
• receiving, using the neural compute engine, updated GAN and/or VAE configuration files with classifications for the type of attack, and mitigation instructions in real time.