Abstract
This thesis presents several methodological and statistical solutions to problems encountered in cyber security. We investigated the effects of compromised data veracity in state estimators and fraud detection systems, a model to impute missing data in attributes of linked observations, and an unsupervised approach to detect infected machines in a computer network.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 7 Jun 2021 |
| Place of Publication | Gouda |
| Print ISBNs | 978-94-6423-299-8 |
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| Publication status | Published - 2021 |
Keywords
- Cybersecurity
- Unsupervised learning
- Imputation
- Data veracity