Method And Systems for Dynamic Spectrum Sharing With A Spectrum Management Firewall

A method of detecting and masking activity of resources in a protected system, comprising:

• collecting, by a processor in a Spectrum Management Firewall (SMF) computing device, data related to the activity of resources within the protected system;
• labeling, by the processor, the collected activity data based on a system type associated with the activity of each resource;
• training, by the processor, a discriminator neural network with the labeled data, wherein the discriminator neural network is configured to evaluate and differentiate between genuine and simulated data related to the activity of the resource;
• configuring, by the processor, a Generative Adversarial Network (GAN) that includes the trained discriminator neural network and a generator neural network that is configured to generate data simulating fake systems related to the type of identified resource or protected system;
• generating, by the processor via the GAN, fake systems related to each type of identified resource or the protected system;
• determining, by the processor, a suitability of each generated fake system for use as a mask based on a credibility of the generated fake system and its ability to obscure real activity of the protected system;
• and
• causing, by the processor, a suitable generated fake system to serve as a mask for the activity of a resource in the protected system.

A non-transitory computer-readable storage medium having stored thereon processor-executable software instructions configured to cause a processor of a computing device implementing a spectrum management firewall (SMF) to perform operations for detecting and masking activity of resources in a protected system, the operations comprising:

• collecting data related to the activity of resources within the protected system;
• labeling the collected activity data based on a system type associated with the activity of each resource;
• training a discriminator neural network with the labeled data, wherein the discriminator neural network is configured to evaluate and differentiate between genuine and simulated data related to the activity of the resource;
• configuring a Generative Adversarial Network (GAN) that includes the trained discriminator neural network and a generator neural network that is configured to generate data simulating fake systems related to the type of identified resource or protected system;
• generating, by the GAN, fake systems related to each type of identified resource or the protected system;
• determining a suitability of each generated fake system for use as a mask based on a credibility of the generated fake system and its ability to obscure real activity of the protected system;
• and
• causing a suitable generated fake system to serve as a mask for the activity of a resource in the protected system.