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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey

Author 1: Noman Mazhar
Author 2: Rosli Salleh
Author 3: Mohammad Asif Hossain
Author 4: Muhammad Zeeshan

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2020.0111283

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 12, 2020.

  • Abstract and Keywords
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Abstract: Internet of things (IoT) is an emerging paradigm that integrates several technologies. IoT network constitutes of many interconnected devices that include various sensors, actu-ators, services and other communicable objects. The increasing demand for IoT and its services have created several security vulnerabilities. Conventional security approaches like intrusion detection systems are not up to the expectation to fulfil the security challenges of IoT networks, due to the conventional technologies used in them. This article presents a survey of intrusion detection and prevention system (IDPS), using state of art technologies, in the context of IoT security. IDPS constitutes of two parts: intrusion detection system and intrusion prevention system. An intrusion detection system (IDS) is used to detect and analyze both inbound and outbound network traffic for malicious activities. An intrusion prevention system (IPS) can be aligned with IDS by proactively inspecting a system’s incoming traffic to mitigate harmful requests. The alignment of IDS and IPS is known as intrusion detection and prevention systems (IDPS). The amalgamation of new technologies, like software-defined network (SDN), machine learning (ML), and manufacturer usage description (MUD), in IDPS is putting the security on the next level. In this study IDPS and its performance benefits are analyzed in the context of IoT security. This survey describes all these prominent technologies in detail and their integrated applications to complement IDPS in the IoT network. Future research directions and challenges of IoT security have been elaborated in the end.

Keywords: Intrusion Detection and Prevention Systems (IDPS); Internet of Things (IoT); Software Defined Network (SDN); Machine Learning (ML); Deep learning (DL); Manufacturer Usage Description (MUD)

Noman Mazhar, Rosli Salleh, Mohammad Asif Hossain and Muhammad Zeeshan, “SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey” International Journal of Advanced Computer Science and Applications(IJACSA), 11(12), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111283

@article{Mazhar2020,
title = {SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111283},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111283},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {12},
author = {Noman Mazhar and Rosli Salleh and Mohammad Asif Hossain and Muhammad Zeeshan}
}


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