An investigation of self-learning and self-protection for Adaptive Digital Twins
| dc.contributor.advisor | Patros, Panos | |
| dc.contributor.advisor | Walmsley, Timothy Gordon | |
| dc.contributor.author | Anderson-Scott, Chris | |
| dc.date.accessioned | 2021-08-23T23:24:25Z | |
| dc.date.available | 2021-08-23T23:24:25Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2021-08-20T05:00:35Z | |
| dc.description.abstract | Adaptive Digital Twins are applicable to a number of fields, including the cybersecurity of industial control systems. This thesis prototypes a Self-Learning adaptive digital twin and posits an architecture for the creation of digital twins based on the learnings gained from the prototype. The prototype shows the efficacy of control theoretical approaches for adaptive digital twins for both modelling and protecting a system, and the architecture posits a generalised method for developing adaptive digital twins. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Anderson-Scott, C. (2021). An investigation of self-learning and self-protection for Adaptive Digital Twins (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/14536 | en |
| dc.identifier.uri | https://hdl.handle.net/10289/14536 | |
| dc.language.iso | en | |
| dc.publisher | The University of Waikato | |
| dc.rights | All items in Research Commons are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated. | |
| dc.subject | Digital twins | |
| dc.subject | Self-learning | |
| dc.subject | Self-protection | |
| dc.subject | Control theory | |
| dc.subject | Process heat | |
| dc.subject | Smart energy systems | |
| dc.subject.lcsh | Computer simulation | |
| dc.subject.lcsh | Software architecture | |
| dc.subject.lcsh | Computer architecture | |
| dc.subject.lcsh | Industrial safety -- Computer simulation | |
| dc.subject.lcsh | Industrial equipment -- Safety measures -- Computer simulation | |
| dc.subject.lcsh | Factories -- Safety measures -- Computer simulation | |
| dc.subject.lcsh | Neural networks (Computer science) | |
| dc.title | An investigation of self-learning and self-protection for Adaptive Digital Twins | |
| dc.type | Thesis | |
| dspace.entity.type | Publication | |
| pubs.place-of-publication | Hamilton, New Zealand | en_NZ |
| thesis.degree.grantor | The University of Waikato | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (Research) (MSc(Research)) |