Intrusion detection system for the internet of things based on blockchain and multi-agent systems

Liang, Chao and Shanmugam, Bharanidharan and Azam, Sami and Karim, Asif and Islam, Ashraful and Zamani, Mazdak and Kavianpour, Sanaz and Idris, Norbik Bashah (2020) Intrusion detection system for the internet of things based on blockchain and multi-agent systems. Electronics (Switzerland), 9 (7). pp. 1-27. ISSN 20799292

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Abstract

With the popularity of Internet of Things (IoT) technology, the security of the IoT network has become an important issue. Traditional intrusion detection systems have their limitations when applied to the IoT network due to resource constraints and the complexity. This research focusses on the design, implementation and testing of an intrusion detection system which uses a hybrid placement strategy based on a multi-agent system, blockchain and deep learning algorithms. The system consists of the following modules: data collection, data management, analysis, and response. The National security lab-knowledge discovery and data mining NSL-KDD dataset is used to test the system. The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment

Item Type:	Article (Journal)
Uncontrolled Keywords:	blockchain; Internet of Things; intrusion detection system; multi-agent system
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Suhani Saarani
Date Deposited:	25 Jan 2021 15:49
Last Modified:	25 Jan 2021 15:49
URI:	http://irep.iium.edu.my/id/eprint/88024

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