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Model inversion attacks reconstruct training data from model outputs, posing privacy risks.
- True
- False
Answer: True
Model inversion exploits model predictions to infer sensitive training data attributes. Mitigation: differential privacy, output perturbation, access controls. Critical for privacy-preserving ML.