Robustness, security and privacy
Attacks on AI systems, the defences, and privacy in machine learning.
- Adversarial examples
- Certified and adversarial robustness
- Distribution shift and OOD
- Jailbreaks
- Prompt injection
- Data poisoning and backdoors
- Model extraction
- Membership and attribute inference
- Differential privacy in ML
- Machine unlearning
- Watermarking and content provenance
- Synthetic media and deepfakes
- Red teaming
- AI supply chain security
- AI threat taxonomies
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