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Probability Analysis of Successful Cyber Attacks in SDN-based Networks.

, , and . NFV-SDN, page 1-6. IEEE, (2018)

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Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-Learning Based Defense Framework., , , , , and . GLOBECOM, page 1-6. IEEE, (2019)Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework., , , , , and . CoRR, (2019)Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network., , , , and . CSoNet, volume 12575 of Lecture Notes in Computer Science, page 26-38. Springer, (2020)A Novel Impact Analysis Approach for SDN-based Networks., , , and . NetSoft, page 10-18. IEEE, (2019)Optimizing resource allocation for elastic security VNFs in the SDNFV-enabled cloud computing., , , , and . ICOIN, page 163-166. IEEE, (2017)A Novel Hybrid Flow-Based Handler with DDoS Attacks in Software-Defined Networking., , and . UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld, page 350-357. IEEE Computer Society, (2016)Probability Analysis of Successful Cyber Attacks in SDN-based Networks., , and . NFV-SDN, page 1-6. IEEE, (2018)On System Stability in Multitier Roadside Computing Toward an Intelligent Transportation., , , , , and . IEEE Trans. Netw. Sci. Eng., 9 (3): 1128-1138 (2022)FEAR: Federated Cyber-Attack Reaction in Distributed Software-Defined Networks with Deep Q-Network., and . WTS, page 1-7. IEEE, (2022)Q-DATA: Enhanced Traffic Flow Monitoring in Software-Defined Networks applying Q-learning., , , and . CNSM, page 1-9. IEEE, (2019)