Improving cyber security in industrial control system environment.
| dc.contributor.advisor | He, Hongmei | |
| dc.contributor.advisor | Tiwari, Ashutosh | |
| dc.contributor.author | Ani, Uchenna Daniel | |
| dc.date.accessioned | 2023-04-13T12:09:06Z | |
| dc.date.available | 2023-04-13T12:09:06Z | |
| dc.date.issued | 2018-02 | |
| dc.description.abstract | Integrating industrial control system (ICS) with information technology (IT) and internet technologies has made industrial control system environments (ICSEs) more vulnerable to cyber-attacks. Increased connectivity has brought about increased security threats, vulnerabilities, and risks in both technology and people (human) constituents of the ICSE. Regardless of existing security solutions which are chiefly tailored towards technical dimensions, cyber-attacks on ICSEs continue to increase with a proportionate level of consequences and impacts. These consequences include system failures or breakdowns, likewise affecting the operations of dependent systems. Impacts often include; marring physical safety, triggering loss of lives, causing huge economic damages, and thwarting the vital missions of productions and businesses. This thesis addresses uncharted solution paths to the above challenges by investigating both technical and human-factor security evaluations to improve cyber security in the ICSE. An ICS testbed, scenario-based, and expert opinion approaches are used to demonstrate and validate cyber-attack feasibility scenarios. To improve security of ICSs, the research provides: (i) an adaptive operational security metrics generation (OSMG) framework for generating suitable security metrics for security evaluations in ICSEs, and a list of good security metrics methodology characteristics (scope-definitive, objective-oriented, reliable, simple, adaptable, and repeatable), (ii) a technical multi-attribute vulnerability (and impact) assessment (MAVCA) methodology that considers and combines dynamic metrics (temporal and environmental) attributes of vulnerabilities with the functional dependency relationship attributes of the vulnerability host components, to achieve a better representation of exploitation impacts on ICSE networks, (iii) a quantitative human-factor security (capability and vulnerability) evaluation model based on human-agent security knowledge and skills, used to identify the most vulnerable human elements, identify the least security aspects of the general workforce, and prioritise security enhancement efforts, and (iv) security risk reduction through critical impact point assessment (S2R-CIPA) process model that demonstrates the combination of technical and human-factor security evaluations to mitigate risks and achieve ICSE-wide security enhancements. The approaches or models of cyber-attack feasibility testing, adaptive security metrication, multi-attribute impact analysis, and workforce security capability evaluations can support security auditors, analysts, managers, and system owners of ICSs to create security strategies and improve cyber incidence response, and thus effectively reduce security risk. | en_UK |
| dc.description.coursename | PhD in Manufacturing | en_UK |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/19453 | |
| dc.language.iso | en | en_UK |
| dc.rights | © Cranfield University, 2015. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | |
| dc.subject | Industrial cyber security | en_UK |
| dc.subject | cyber-physical system security | en_UK |
| dc.subject | cyber security evaluation | en_UK |
| dc.subject | security impact analysis | en_UK |
| dc.subject | operational security metrics | en_UK |
| dc.subject | human-factor security | en_UK |
| dc.subject | functional dependency analysis | en_UK |
| dc.subject | security criticality analysis | en_UK |
| dc.subject | security risk assessment | en_UK |
| dc.title | Improving cyber security in industrial control system environment. | en_UK |
| dc.type | Thesis | en_UK |