Detecting Saturation Attacks in SDN via Machine Learning-Reference-Cited by-同舟云学术

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Detecting Saturation Attacks in SDN via Machine Learning

Published:2019-10 Issue: Volume: Page:
ISSN:
Container-title:2019 4th International Conference on Computing, Communications and Security (ICCCS)
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Author:

Khamaiseh Samer,Serra Edoardo,Li Zhiyuan,Xu Dianxiang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8883094/8888030/08888049.pdf?arnumber=8888049

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. TITAN: Combining a bidirectional forwarding graph and GCN to detect saturation attack targeted at SDN;PLOS ONE;2024-04-26

2. Detection and Categorization of Conflict Flows Within SDN Environments using Machine Learning Approach;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

3. A Comprehensive Survey on Knowledge-Defined Networking;Telecom;2023-08-02

4. Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions;SECURITY AND PRIVACY;2023-07-30

5. Deep learning for the security of software-defined networks: a review;Cluster Computing;2023-07-15

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