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Title	Software Defined Network Security Framework For Iot Based Smart Home And City Applications
ID_Doc	52158
Authors	Wang S.; Gomez K.M.; Sithamparanathan K.; Zanna P.
Year	2019
Published	2019, 13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019 - Proceedings
DOI	http://dx.doi.org/10.1109/ICSPCS47537.2019.9008703
Abstract	As a popular application of Internet of Things (IoT), Smart City Frameworks aim to provide real time tracking, intelligent control and surveillance across the city. Thus the improvement of resource utilization is a big concern in the management, how to administer such a massive network to meet the requirement of different services? Software Defined Network (SDN) is an ideal solution in customizing networks; however the security feature is the common challenge in both SDN and IoT. In this paper, we propose a framework that uses smart techniques for improving the security features of SDN for smart city applications and diminishing the risk of network invasion. Our SDN Security Framework (SDN-SF) combines two techniques: i) it restrains the unnecessary path between IoT nodes, and ii) it classifies devices into three levels from a combination of MAC address and HTTP request. Additionally, thresholds derived from historical behavior are used for anomaly detection in order to enhance network adaptation. Our result collected from real SDN-based IoT testbed demonstrates that our SDN-SF for Smart City scenarios is able to detect and mitigate malicious traffic with 99.9% of detection rate and 0.5-1 second of detection time in both the control and data plane, respectively. © 2019 IEEE.
Author Keywords	Anomaly Detection; IoT; Network Attacks; SDN; Security; Smart City

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