Improving security of autonomous cyber-physical systems against adversarial examples
Deep learning, enabled by the advancements of hardware accelerators, is increasingly employed in cyber-physical systems due to its capabilities in capturing sophisticated patterns from complex physical processes. However, deep learning is shown susceptible to adversarial examples, which are crafted...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/161165 |