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A Secure Fog-based Platform for SCADA-based IoT Critical Infrastructure

Shamsa, TB, Asim, M, Mac Dermott, AM, Iqbal, F, Kamoun, F, Shah, B, Alfandi, O and Hammoudeh, M A Secure Fog-based Platform for SCADA-based IoT Critical Infrastructure. Software: Practice and Experience. ISSN 0038-0644 (Accepted)

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Abstract

The rapid proliferation of Internet of Things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures and control systems has put stringent performance and scalability requirements on modern Supervisory Control and Data Acquisition (SCADA) systems. While cloud computing has enabled modern SCADA systems to cope with the increasing amount of data generated by sensors, actuators and control devices, there has been a growing interest recently to deploy edge datacenters in fog architectures to secure low-latency and enhanced security for mission-critical data. However, fog security and privacy for SCADA-based IoT critical infrastructures remains an under-researched area. To address this challenge, this contribution proposes a novel security “toolbox” to reinforce the integrity, security, and privacy of SCADA-based IoTcritical infrastructure at the fog layer. The toolbox incorporates a key feature: a cryptographic-based access approach to the cloud services using identity-based cryptography and signature schemes at the fog layer. We present the implementation details of a prototype for our proposed Secure Fog-based Platform (SeFoP) and provide performance evaluation results to demonstrate the appropriateness of the proposed platform in a real-world scenario. These results can pave the way towards the development of more secured and trusted SCADA-based IoT critical infrastructure, which is essential to counter cyber threats against next-generation critical infrastructure and industrial control systems. The results from the experiments demonstrate a superior performance of SeFoP, which is around 2.8 seconds when adding 5 virtual machines (VMs), 3.2 seconds when adding 10 VMs, and 112 seconds when adding 1000 VMs compared to Multi-Level user Access Control (MLAC) platform.

Item Type: Article
Uncontrolled Keywords: 08 Information and Computing Sciences, 17 Psychology and Cognitive Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: Wiley
Date Deposited: 06 Feb 2019 08:58
Last Modified: 08 Feb 2019 15:41
URI: http://researchonline.ljmu.ac.uk/id/eprint/10116

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