Cloud-based Autonomic Computing Framework for Securing SCADA Systems
Book chapter
Patel, S., Patel, D. and Nazir, S. (2020). Cloud-based Autonomic Computing Framework for Securing SCADA Systems. in: Chui, K.T., Lytras, M.D., Liu, R.W. and Zhao, M. (ed.) Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence IGI Global.
Authors | Patel, S., Patel, D. and Nazir, S. |
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Editors | Chui, K.T., Lytras, M.D., Liu, R.W. and Zhao, M. |
Abstract | This chapter proposes an autonomic computing security framework for protecting cloud-based SCADA systems against cyber threats. Autonomic computing paradigm is based on intelligent computing that can autonomously take actions under given conditions. These technologies have been successfully applied to many problem domains requiring autonomous operations. One such area of national interest is SCADA systems that monitor critical infrastructures such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks. The SCADA systems have evolved from isolated systems into a complex, highly connected systems requiring constant availability. The migration of such systems from in-house to cloud infrastructures has gradually gained prominence. The deployments over cloud infrastructures have brought new cyber security threats, challenges and mitigation opportunities. SCADA deployment to cloud makes it imperative to adopt newer architectures and measures that can proactively and autonomously react to an impending threat. |
Keywords | Autonomic computing framework; cloud SCADA; cyber security; communications; critical infrastructures; hybrid cloud |
Year | 2020 |
Book title | Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence |
Publisher | IGI Global |
File | License File Access Level Open |
ISBN | 978-1799830382 |
Publication dates | |
03 Jan 2020 | |
Publication process dates | |
Accepted | 01 Dec 2019 |
Deposited | 09 Jan 2020 |
Digital Object Identifier (DOI) | https://doi.org/10.4018/978-1-7998-3038-2 |
https://openresearch.lsbu.ac.uk/item/88w56
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