Computer-implemented system and method for cybersecurity threat analysis using federated machine learning and hierarchical task networks

Abstract

A system and method for cyber exploitation path analysis and response using federated networks to minimize network exposure and maximize network resilience, with the ability to simulate complex and large scale network traffic through the use of federated training networks, by gathering network entity information, establishing baseline behaviors for each entity, and monitoring each entity for behavioral anomalies that might indicate cybersecurity concerns. Further, the system and method involve incorporating network topology information into the analysis by generating a model of the network, annotating the model with risk and criticality information for each entity in the model and with a vulnerability level between entities, and using the model to evaluate cybersecurity risks to the network. Lastly, network attack path analysis and automated task planning for minimizing network exposure and maximizing resiliency is performed with machine learning, generative adversarial networks, hierarchical task networks, and Monte Carlo search trees.