Improved Automated Graph and FCM Based DDoS Attack Detection Mechanism in Software Defined Networks

Xin Li,
Zhijie Fan,
Ya Xiao,
Qian Xu,
Wenye Zhu,

Abstract


The DDoS attack is an unneglected cyber security threats in Software Defined Networks, specially it can have a fatal impact on SDNs. In this paper, we propose an improved automated graph based DDoS attack detection mechanism based on Fuzzy Cognitive Map (FCM) on SDNs. With the network patterns as nodes and similarity as link weights, our model based on feature-pattern graph and FCM is capable of detecting the DDoS attacks using graph based our method, and it can also scalable to insert new nodes to the graph model by graph update according to the unknown attack threats that are tried to find automatically. Our experimental results shown that the feasibility of our proposed method is a more accurate way to detect the DDoS attack by comparing with other similar methods.


Citation Format:
Xin Li, Zhijie Fan, Ya Xiao, Qian Xu, Wenye Zhu, "Improved Automated Graph and FCM Based DDoS Attack Detection Mechanism in Software Defined Networks," Journal of Internet Technology, vol. 20, no. 7 , pp. 2117-2127, Dec. 2019.

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Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
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