Security News > 2021 > April > Microsoft Open-Sources 'CyberBattleSim' Enterprise Environment Simulator
Designed to help advance artificial intelligence and machine learning, the experimental research project was designed to aid in the analysis of how "Autonomous agents operate in a simulated enterprise environment using high-level abstraction of computer networks and cybersecurity concepts."
Reinforcement learning, Microsoft explains, is a type of machine learning that teaches autonomous agents to make decisions based on the interaction with the environment: agents improve strategies through repeated experience, similarly to playing a video game over and over to become better at it.
In software security, reinforcement learning involves the use of agents that play the role of attackers and defenders, and the analysis of their evolution in the simulated environment.
"The simulation Gym environment is parameterized by the definition of the network layout, the list of supported vulnerabilities, and the nodes where they are planted. The simulation does not support machine code execution, and thus no security exploit actually takes place in it," Microsoft explains.
Using the Gym interface, defenders can instantiate automated agents and then analyze their evolution in the environment.
Microsoft says CyberBattleSim has a highly abstract nature and cannot be applied to real-world systems, which provides protection against the nefarious use of the trained automated agents.