unica-mlsec/mlsec

PhD/MSc course on Machine Learning Security (Univ. Cagliari)

40
/ 100
Emerging

This course material provides an in-depth understanding of how to secure machine learning systems. It covers threat modeling, various types of attacks like evasion and poisoning, and strategies for defending against them. The content helps students evaluate the robustness of AI models and design more secure ones. This resource is for master's and PhD students in computer engineering, cybersecurity, and artificial intelligence.

225 stars.

Use this if you are a graduate student or researcher looking to deeply understand and implement security measures for machine learning models.

Not ideal if you are looking for a quick introduction to machine learning basics or a tool for immediate, practical model deployment without security considerations.

cybersecurity artificial-intelligence machine-learning-engineering threat-analysis adversarial-robustness
No License No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 16 / 25

How are scores calculated?

Stars

225

Forks

26

Language

Jupyter Notebook

License

Category

ai-red-teaming

Last pushed

Dec 18, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/unica-mlsec/mlsec"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.