Flow-based anomaly intrusion detection using machine learning model with software defined networking for OpenFlow network

Author:

Satheesh N.,Rathnamma M.V.,Rajeshkumar G.,Sagar P. Vidya,Dadheech Pankaj,Dogiwal S.R.,Velayutham Priya,Sengan Sudhakar

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Software

Reference48 articles.

1. Maturing of OpenFlow and software-defined networking through deployments;Kobayashi;Computer Netw.,2014

2. Tang, T., Zaidi, S.A.R., McLernon, D., Mhamdi, L., Ghogho, M., Deep recurrent neural network for intrusion detection in SDN-based networks. In 2018 IEEE International Conference on Network Softwarization (NetSoft 2018), Montreal, Canada, Jun 2018.

3. An improved network security situation assessment approach in software-defined networks;Fan;Peer-to-Peer Netw. Appl.,2017

4. A deep learning-based DDoS detection system in software-defined networking (SDN);Niyaz;EAI Endorsed Trans. Secur. Saf.,2017

5. An SDN approach: quality of service using big switches floodlight open-source controller;Wallner;Proc. Asia-Pac. Adv. Netw.,2013

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