Defending against model extraction attacks via watermark-based method with knowledge distillation
Developing deep neural network (DNN) models often requires significant investment in computational resources, expertise, and vast amount of data. The increasing popularity of Machine Learning as a Service (MLaaS) offers convenient access to these powerful models, but it also raises concerns about In...
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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/10356/176640 |