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Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security

Derhab, Abdelouahid; Guerroumi, Mohamed; Gumaei, Abdu; Maglaras, Leandros; Ferrag, Mohamed Amine; Mukherjee, Mithun; Khan, Farrukh Aslam

Authors

Abdelouahid Derhab

Mohamed Guerroumi

Abdu Gumaei

Mohamed Amine Ferrag

Mithun Mukherjee

Farrukh Aslam Khan



Abstract

The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be adopted. In this paper, we focus on the security of commands in industrial IoT against forged commands and misrouting of commands. To this end, we propose a security architecture that integrates the Blockchain and the Software-defined network (SDN) technologies. The proposed security architecture is composed of: (a) an intrusion detection system, namely RSL-KNN, which combines the Random Subspace Learning (RSL) and K-Nearest Neighbor (KNN) to defend against the forged commands, which target the industrial control process, and (b) a Blockchain-based Integrity Checking System (BICS), which can prevent the misrouting attack, which tampers with the OpenFlow rules of the SDN-enabled industrial IoT systems. We test the proposed security solution on an Industrial Control System Cyber attack Dataset and on an experimental platform combining software-defined networking and blockchain technologies. The evaluation results demonstrate the effectiveness and efficiency of the proposed security solution.

Citation

Derhab, A., Guerroumi, M., Gumaei, A., Maglaras, L., Ferrag, M. A., Mukherjee, M., & Khan, F. A. (2019). Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security. Sensors, 19(14), Article 3119. https://doi.org/10.3390/s19143119

Journal Article Type Article
Acceptance Date Jul 12, 2019
Online Publication Date Jul 15, 2019
Publication Date 2019
Deposit Date Jan 6, 2023
Publicly Available Date Mar 29, 2024
Journal Sensors
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 19
Issue 14
Article Number 3119
DOI https://doi.org/10.3390/s19143119
Keywords industrial IoT; industrial control system; SCADA; distributed control system; blockchain; software-defined network; random subspace learning; intrusion detection system; security
Public URL http://researchrepository.napier.ac.uk/Output/2969477

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