| Inhalt |
The lecture Machine Learning Security (MLS) covers multiple kinds of relations between machine learning (ML) and IT security. After a recap of the fundamentals of both of these fields, we discuss three roles of ML in IT security: ML as defense, ML as victim, and ML as attack tool. Finally, we will look at methods to securing ML. |
| Lernziele |
At completion of the course, you will:
- understand existing threats to ML as well as possible countermeasures,
- understand the application of ML in security,
- be able to implement robust and secure machine-learning systems,
- have developed practical skills in using ML-based tools for solving real-world problems in security,
- be able to evaluate ML models for their security robustness.
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