EVADE: Efficient Moving Target Defense for Autonomous Network Topology Shuffling Using Deep Reinforcement Learning

Qisheng Zhang, Jin-Hee Cho, Terrence J. Moore, Dan Dongseong Kim, Hyuk Lim, Frederica Free-Nelson. EVADE: Efficient Moving Target Defense for Autonomous Network Topology Shuffling Using Deep Reinforcement Learning. In Mehdi Tibouchi, Xiaofeng Wang 0006, editors, Applied Cryptography and Network Security - 21st International Conference, ACNS 2023, Kyoto, Japan, June 19-22, 2023, Proceedings, Part I. Volume 13905 of Lecture Notes in Computer Science, pages 555-582, Springer, 2023. [doi]

Abstract

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