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Secure SDN Traffic based on Machine Learning Classifier
Nowadays, the majority of human activities are carried out utilizing a variety of services or applications that rely on the local and Internet connectivity services provided by private or public networks. With the developments in Machine Learning and Software Defined Networking, traffic classification has become an essential study subject. As a consequence of the segregation of control and data planes, Software Defined Networks have some security flaws. To cope with malicious code in SDN,doi:10.5281/zenodo.6786157 fatcat:l3ywm4wwc5dwnbfkxg6hl7arii