Detecting P2P Botnet in Software Defined Networks

Shang Chiuan Su, Yi Ren Chen, Shi-Chun Tsai*, Yi-Bing Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Software Defined Network separates the control plane from network equipment and has great advantage in network management as compared with traditional approaches. With this paradigm, the security issues persist to exist and could become even worse because of the flexibility on handling the packets. In this paper we propose an effective framework by integrating SDN and machine learning to detect and categorize P2P network traffics. This work provides experimental evidence showing that our approach can automatically analyze network traffic and flexibly change flow entries in OpenFlow switches through the SDN controller. This can effectively help the network administrators manage related security problems.

Original languageEnglish
Article number4723862
JournalSecurity and Communication Networks
StatePublished - 1 Jan 2018

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