Clustering of IoT Devices Using Device Profiling and Behavioral Analysis to Build Efficient Network Policies

  • Muhammad Hamza University Institute of Information Technology, PMAS- Arid Agriculture University, Rawalpindi, Pakistan.
  • Syed Mashhad M. Geelani University Institute of Information Technology, PMAS- Arid Agriculture University, Rawalpindi, Pakistan.
  • Qamar Nawaz Department of Computer Science, The University of Agriculture, Faisalabad, Pakistan.
  • Asif Kabir Department of Computer Science and Information Technology, University of Kotli, AJK, Pakistan.
  • Isma Hamid Department of Computer Science, National Textile University, Faisalabad, Pakistan.

Abstract

The Internet of Things (IoT) has emerged as a new paradigm, and billions of devices are connected with the internet. IoT is being penetrated in major domains of daily life like health care, agriculture, industry, smart homes and monitoring of the environment. The operator of such complex, huge and diverse heterogeneous networks may not even be fully aware of their IoT devices working, activity, behavior and resource utilization etc. The efficient management of IoT devices becomes a challenge for network managers to ensure smooth network operation. Network traffic analysis of IoT devices is a necessary and rudimentary tool to understand the behavior of devices. In this paper firstly, we identify insights of device network traffic, discuss the activity patterns of some IoT devices and present a visual description of the pattern of IoT devices. Secondly, after analyzing the device's behavior, we build and demonstrate a profile of each device based on its activity cycle and traffic patterns information. Thirdly, the K-Means clustering algorithm is used to make clusters of IoT devices using their profile information. The clustering algorithm groups similar devices in a single group. The obtained results clearly describe the patterns of devices which help the network managers to make appropriate network policies for efficient secure network management.

Published
Apr 1, 2021
How to Cite
HAMZA, Muhammad et al. Clustering of IoT Devices Using Device Profiling and Behavioral Analysis to Build Efficient Network Policies. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 40, n. 2, p. 335 - 345, apr. 2021. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/2086>. Date accessed: 19 june 2021. doi: http://dx.doi.org/10.22581/muet1982.2102.08.
Section
Articles
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License