2026-09-19T04:56:31Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1431912022-06-16T03:01:39Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Siegel, Michael
Esteban, Jonathan
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-06-15T13:02:28Z
2022-06-15T13:02:28Z
2022-02
2022-02-22T18:31:54.831Z
https://hdl.handle.net/1721.1/143191
Modern cyber attacks demand immediate action plans based on an overwhelming amount of information and options. Microsoft has made available a highly parameterizable model of enterprise networks with the capability of simulating automated cyber-attacks. We provide an extension of this project by means of a web platform. The platform allows a user to model an enterprise network topology, interact with the topology manually, and simulate an automated adversarial agent. Leveraging the CyberBattleSim toolkit, we enable the swift prototyping of different network configurations that can then be analyzed by a defensive security team member either manually or automatically through the automated agent. We demonstrate that the platform can simulate any network topology supported by CyberBattleSim as well as evaluate different Q-Learning strategies. This in turn can provide us with valuable insight regarding the progression of cyber attacks, aiding us at generating appropriate cyber-attack response plans.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Simulating Network Lateral Movements through the CyberBattleSim Web Platform
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>Modern cyber attacks demand immediate action plans based on an overwhelming amount of information and options. Microsoft has made available a highly parameterizable model of enterprise networks with the capability of simulating automated cyber-attacks. We provide an extension of this project by means of a web platform. The platform allows a user to model an enterprise network topology, interact with the topology manually, and simulate an automated adversarial agent. Leveraging the CyberBattleSim toolkit, we enable the swift prototyping of different network configurations that can then be analyzed by a defensive security team member either manually or automatically through the automated agent. We demonstrate that the platform can simulate any network topology supported by CyberBattleSim as well as evaluate different Q-Learning strategies. This in turn can provide us with valuable insight regarding the progression of cyber attacks, aiding us at generating appropriate cyber-attack response plans.</Abstract>
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