Abstract
By the growth of software-defined networks (SDN), the SDN separated the switching and routing function. It is classified in the data and control plane, respectively. In general, the control plane is centralized and is responsible for deciding what to do when a new incoming packet arrives. When making a decision, it is saved on the data plane in the switch forwarding table. The SDN has several advantages of centralized management, programming, vendor neutrality, and agility. It can be hit by a denial of service attack (DDoS). For detection and prevention attacks of DDoS, we proposed a model to detect and prevent attacks of DDoS in the SDN by using machine learning algorithms. The model extracts multi-features from the packet-in messages in the controller and analyzed by utilization entropy and then utilizes the trained algorithms to detect and prevent the attacks of DDoS. The experiments show that the Hoeffding trees can detect DDoS attacks in real time with high efficiency. Blockchain technology is very efficient in data security from hackers to see and steal critical data.KeywordsSoftware-defined network (SDN)DDoSBlockchain technologyMachine learningData security
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