Robustifying Machine Learning based Security Applications
In recent years, machine learning (ML) has been explored and employed in many fields. However, there are growing concerns about the robustness of machine learning models. These concerns are further amplified in security-critical applications — attackers can manipulate the inputs (i.e., adversarial e...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Others |
| Published: |
Virginia Tech
2020
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10919/99862 |