EVADE: Efficient Moving Target Defense for Autonomous Network Topology Shuffling Using Deep Reinforcement Learning - researchr publication authors

researchr

You are not signed in
Sign in
Sign up

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]

This author has not been identified. Look up 'Qisheng Zhang' in GoogleThis author has not been identified. Look up 'Jin-Hee Cho' in GoogleThis author has not been identified. Look up 'Terrence J. Moore' in GoogleThis author has not been identified. Look up 'Dan Dongseong Kim' in GoogleThis author has not been identified. Look up 'Hyuk Lim' in GoogleThis author has not been identified. Look up 'Frederica Free-Nelson' in Google

runs on WebDSL