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Title	Intelligent Threat Hunting In Software-Defined Networking
ID_Doc	32590
Authors	Schmitt S.; Kandah F.I.; Brownell D.
Year	2019
Published	2019 IEEE International Conference on Consumer Electronics, ICCE 2019
DOI	http://dx.doi.org/10.1109/ICCE.2019.8661952
Abstract	The emergence of Software-Defined Networking (SDN) has brought along a wave of new technologies and developments in the field of networking with hopes of dealing with network resources more efficiently and providing a foundation of programmability. SDN allows for both flexibility and adaptability by separating the control and data planes in a network environment by virtualizing network hardware. We, in this work, present an advanced threat hunting model by combining the SDN infrastructure with threat hunting techniques and machine learning models aiming to intelligently handle network threats such as denial of Service, repeat, and main in the middle attacks. This advancement enables the handling of dynamic network traffic in areas such as smart cities and autonomous vehicles more efficiently by rapidly mitigating network threats. © 2019 IEEE.
Author Keywords	Pattern mining; Software-defined networking; Threat hunting

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