Microsoft has produced a cyberattack simulator that’s made to enable safety researchers to produce simulated network environments in get to notice the interactions involving automatic Artificial Intelligence (AI)-pushed attackers and defenders.
The simulator called CyberBattleSim, is readily available under an open resource license and depends on the Python-centered Open AI Gymnasium toolkit to train the automatic brokers centered on reinforcement mastering algorithms.
“To stay forward of adversaries, who display no restraint in adopting tools and strategies that can help them attain their targets, Microsoft proceeds to harness AI and equipment mastering to solve security problems. A single spot we have been experimenting on is autonomous programs,” writes William Blum from Microsoft 365 Defender Exploration Workforce even though introducing the simulator.
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Blum explains that CyberBattleSim helps researchers observe and understand how a threat actor laterally spreads through a network after its initial compromise.
The simulator is part of Microsoft’s efforts to use AI and machine learning in its battle against adversaries.
Security researchers can use the open sourced simulator to create a network with several nodes along with their running services, their vulnerabilities, as well as the security mechanisms on individual nodes.
The simulator tasks the automated attackers to take ownership of as much of the network by exploiting the vulnerabilities of the nodes. Similarly, automated defenders are designed to detect the presence of the attackers and eject them from the network in order to contain the attack.
Blum hopes the security community can use this simulator to refine the use of reinforcement learning for security applications.
“With CyberBattleSim, we are just scratching the surface of what we believe is a huge potential for applying reinforcement learning to security. We invite researchers and data scientists to build on our experimentation,” he concludes.