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Autonomous Cyber Operations (ACO) involves the development of blue team (defender) and red team (attacker) decision-making agents in adversarial scenarios.
Large-scale virtualization in the Emulab network testbed
M Hibler R Ricci L Stoller, Jonathon Duerig, Shashi Guruprasad, Tim Stack, Kirk Webb, and Jay Lepreau · 2008
Earlier work this paper cites.
Simulating cyber-attacks for fun and profit
Ariel Futoransky, Fernando Miranda, José Orlicki, and Carlos Sarraute · 2010
Earlier work this paper cites.
The DETER project: Advancing the science of cyber security experimentation and test
Jelena Mirkovic, Terry V Benzel, Ted Faber, Robert Braden, John T Wroclawski, and Stephen Schwab · 2010
Earlier work this paper cites.
Intelligence-driven computer network defense informed by analysis of adversary campaigns and intrusion kill chains
Eric M Hutchins, Michael J Cloppert, Rohan M Amin, et al · 2011
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Metasploit toolkit for penetration testing, exploit development, and vulnerability research
David Maynor · 2011
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VINE: A cyber emulation environment for mtd experimentation
Thomas C Eskridge, Marco M Carvalho, Evan Stoner, Troy Toggweiler, and Adrian Granados · 2015
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Deep recurrent q-learning for partially observable mdps
Matthew J. Hausknecht and Peter Stone · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
Earlier work this paper cites.
Coevolutionary agent-based network defense lightweight event system (CANDLES)
George Rush, Daniel R Tauritz, and Alexander D Kent · 2015
Cited alongside, same era.
Intelligent, automated red team emulation
Andy Applebaum, Doug Miller, Blake Strom, Chris Korban, and Ross Wolf · 2016
Cited alongside, same era.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Cited alongside, same era.
Validation of network simulation model and scalability tests using example malware
Scott Brown, Harold Brown, Michael Russell, Brian Henz, Michael Edwards, Frank Turner, and Giorgio Bertoli · 2016
Cited alongside, same era.
Simulation-based design of dynamic controllers for humanoid balancing
Jie Tan, Zhaoming Xie, Byron Boots, and C. Karen Liu · 2016
Cited alongside, same era.
Reinforcement learning vs genetic algorithms in game-theoretic cyber-security, Oct 2018
S. Niculae · 2018
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Galaxy: A network emulation framework for cybersecurity
Kevin Schoonover, Eric Michalak, Sean Harris, Adam Gausmann, Hannah Reinbolt, Daniel R Tauritz, Chris Rawlings, and Aaron Scott Pope · 2018
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Autonomous Penetration Testing using Reinforcement Learning
J. Schwartz and H. Kurniawati · 2019
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Live Response Training Range mit Velociraptor
Sinthujan Lohanathan and Severin Marti · 2020
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How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, and Sergey Levine · 2021
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A cloud-based platform for the emulation of complex cybersecurity scenarios
Angelo Furfaro, Antonio Piccolo, Andrea Parise, Luciano Argento, and Domenico Sacca · 2018
Cited alongside, same era.
Automated adversary emulation: A case for planning and acting with unknowns
Doug Miller, Ron Alford, Andy Applebaum, Henry Foster, Caleb Little, and Blake Strom · 2018
Cited alongside, same era.
Andres Molina-Markham, Cory Miniter, Becky Powell, and Ahmad Ridley · 2021
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Cyberbattlesim
Microsoft Defender Research Team · 2021
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