Enhancement in Securing Open Source SDN Controller Against DDoS Attack
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6586-1_27
Reference19 articles.
1. Yang L, Zhao H (2018) DDoS attack identification and defense using SDN based on machine learning method. In: 2018 15th international symposium on pervasive systems, algorithms and networks (I-SPAN), Yichang, pp 174–178. https://doi.org/10.1109/I-SPAN.2018.00036
2. Somani G et al (2017) DDoS attacks in cloud computing: issues, taxonomy, and future directions. Comput Commun 107:30–48. ISSN 01403664. https://doi.org/10.1016/j.comcom.2017.03.010
3. Luong T-K, Tran T-D, Le G-T (2020) DDoS attack detection and defense in SDN based on machine learning. In: National conference on information and computer science (NICS). https://doi.org/10.1109/NICS51282.2020.9335867
4. Virushabadoss S, Anithaashri TP (2022) Enhancing data security in mobile cloud using novel key generation. Proc Comput Sci 215:567–576. ISSN 1877-0509. https://doi.org/10.1016/j.procs.2022.12.059
5. Eliyan LF, Di Pietro R (2021) DoS and DDoS attacks in software defined networks: a survey of existing solutions and research challenges. Future Gen Comput Syst 122:149–171. ISSN 0167-739X. https://doi.org/10.1016/j.future.2021.03.011
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