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Badri, S, Fergus, P and Hurst, W (2016) Critical Infrastructure Automated Immuno-Response System (CIAIRS). In: 2016 International Conference on Control, Decision and Information Technologies (CoDIT) . (The 3rd International Conference on Control, Decision and Information Technologies, 06 April 2016 - 08 April 2016, Malta).
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Abstract
Over the last decade, critical infrastructures have become increasingly complex. They now possess levels of automation which requires the integration of, often, mutually incompatible technologies. In addition, the data sets generated are t, vast and intricate level of interdependency between infrastructures has grown. Any failures, caused by cyber-attacks, have the ability to spread through a system of systems and are a challenge to detect. Therefore, this paper firstly discusses the interdependency challenges facing critical infrastructures; and how it can be used towards creating a support network against cyber-attacks. In much the same way as the human immune system is able to respond to intrusion, our proposed system is able to detect cyber-attacks and share the knowledge with interconnected partners. In order to demonstrate our approach, a simulation framework of 8 critical infrastructures is presented. Furthermore, our big data analysis techniques, used to identify and share threats between infrastructures, are discussed in depth.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Computer Science and Mathematics |
| Publisher: | IEEE |
| Date Deposited: | 26 Feb 2016 12:34 |
| Last Modified: | 16 May 2024 12:49 |
| DOI or ID number: | 10.1109/CoDIT.2016.7593542 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/2999 |
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