Review of adversarial attacks and defenses on edge machine learning
This project aims to analyse the various Adversarial Threats to Machine Learning on the Edge and how they can be mitigated by Trusted Execution Environment (TEE). This report will analyse the effectiveness of the TEE in mitigating these threats and where it can be supplemented by other Adversarial D...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175152 |
| Summary: | This project aims to analyse the various Adversarial Threats to Machine Learning on the Edge and how they can be mitigated by Trusted Execution Environment (TEE). This report will analyse the effectiveness of the TEE in mitigating these threats and where it can be supplemented by other Adversarial Defenses in the Edge setting. |
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