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Software Defined Network Security Framework for IoT based Smart Home and City Applications

conference contribution
posted on 2024-11-03, 13:32 authored by Song Wang, Karina Mabell Gomez Chavez, Kandeepan SithamparanathanKandeepan Sithamparanathan, Paul Zanna
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.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1109/ICSPCS47537.2019.9008703
  2. 2.
    ISBN - Is published in 9781728121956 (urn:isbn:9781728121956)

Number

9008703

Start page

588

End page

595

Total pages

8

Outlet

Proceedings of the 13th International Conference on Signal Processing and Communication Systems (ICSPCS 2019)

Name of conference

ICSPCS 2019

Publisher

IEEE

Place published

United States

Start date

2019-12-16

End date

2019-12-18

Language

English

Copyright

© 2019 IEEE.

Former Identifier

2006106391

Esploro creation date

2022-11-12

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