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All issues Volume 218 (2018) MATEC Web Conf., 218 (2018) 02012 References
Open Access
Issue
MATEC Web Conf.
Volume 218, 2018
The 1st International Conference on Industrial, Electrical and Electronics (ICIEE 2018)
Article Number 02012
Number of page(s) 8
Section Control Electronics, Circuits, and Systems
DOI https://doi.org/10.1051/matecconf/201821802012
Published online 26 October 2018
  1. J. Chen, X. Zheng, and C. Rong, “Survey on software-defined networking,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 9106, no. 1, pp. 115–124, (2015). [Google Scholar]
  2. D. Kreutz and F. Ramos, “Software-Defined Networking: A Comprehensive Survey,” arXiv Prepr. arXiv …, p. 49, (2014). [Google Scholar]
  3. A. Samson and N. P. Gopalan, “Software Defined Networking,” Proc. Int. Conf. Informatics Anal. - ICIA-16, pp. 1–6, (2016). [Google Scholar]
  4. S. . A. Scott-Hayward, S.a, Natarajan, S.b, Sezer, “Survey of Security in Software Defined Networks,” Surv. Tutorials, vol. 18, no. 1, pp. 623–654, (2016). [CrossRef] [Google Scholar]
  5. H. D. Zubaydi and M. Anbar, “Review on Detection Techniques against DDoS Attacks on a Software-Defined Networking Controller,” (2017). [Google Scholar]
  6. A. X. Liu, “l An Advanced Entropy-Based DDOS Detection Scheme Jie Zhang, Zheng Qin, Lu Ou, Pei Jiang, JianRong Liu,” pp. 67–71, (2010). [Google Scholar]
  7. M. Jackson, D. Nelson, and S. Stirk, Lecture Notes in Computer Science. (2005). [CrossRef] [Google Scholar]
  8. S. M. Mousavi and M. St-Hilaire, “Early detection of DDoS attacks against SDN controllers,” 2015 Int. Conf. Comput. Netw. Commun. ICNC 2015, pp. 77–81, (2015). [Google Scholar]
  9. Y. Jiang, X. Zhang, Q. Zhou, and Z. Cheng, “An Entropy-Based DDoS Defense Mechanism in Software Defined Networks,” in International Conference on Communicatins and Networking in China, pp. 169–178, (2016) [Google Scholar]
  10. A. S. Syed Navaz, V. Sangeetha, and C. Prabhadevi, “Entropy based Anomaly Detection System to Prevent DDoS Attacks in Cloud,” Int. J. Comput. Appl., vol. 62, no. 15, pp. 975–8887, (2013). [Google Scholar]
  11. G. A. Ajaeiya and A. F. B. Ids, “Flow-Based Intrusion Detection System for SDN,” pp. 787--793, (2017). [Google Scholar]
  12. P. Dong, X. Du, H. Zhang, and T. Xu, “A detection method for a novel DDoS attack against SDN controllers by vast new low-traffic flows,” 2016 IEEE Int. Conf. Commun. ICC 2016, (2016). [Google Scholar]
  13. J. Luo, X. Yang, J. Wang, J. Xu, J. Sun, and K. Long, “On a mathematical model for low-rate shrew DDoS,” IEEE Trans. Inf. Forensics Secur., vol. 9, no. 7, pp. 1069–1083, (2014). [CrossRef] [Google Scholar]
  14. M. Nugraha, I. Paramita, A. Musa, D. Choi, and B. Cho, “Utilizing OpenFlow and sFlow to Detect and Mitigate SYN Flooding Attack TT -,” J. Korea Multimed. Soc., vol. 17, no. 8, pp. 988–994, (2014). [CrossRef] [Google Scholar]

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