Stephen J Melsom

US Patent:

20200364347, Nov 19, 2020

Filed:

May 1, 2020

Appl. No.:

16/864826

Inventors:

- Reston VA, US
Jason Adam DEICH - Arlington VA, US
Stephen John MELSOM - Reston VA, US
Kara Jean DODENHOFF - Reston VA, US
William Tyler NIGGEL - Wilmington NC, US

Assignee:

NOBLIS, INC. - Reston VA

International Classification:

G06F 21/57
G06F 21/56

Abstract:

An adversarial reinforcement learning system is used to simulate a security checkpoint. The system includes a simulation engine configured to simulate a security checkpoint and various threat objects and threat-mitigation objects therein. The system further includes an attack model configured to control threat objects in the simulation and a defense model configured to control threat-mitigation objects in the simulation. A first portion of the simulation is executed by the simulation engine in order to generate an outcome of the first portion of the simulation. The defense model then generates a threat-mitigation input to control threat-mitigation objects in a subsequent portion of the simulation, and the attack model then generates a threat input to control threat objects in the subsequent portion of the simulation, wherein the inputs are based in part on the outcome of the first portion of the simulation.