Which of the following is the BEST technique to mitigate a model inversion attack?
Model inversion is a privacy attack that seeks to infer sensitive information about training data from a model. Privacy-preserving methods, particularly techniques such as differential privacy that limit information leakage, directly mitigate this risk. NIST classifies privacy attacks as attempts to learn sensitive information about an AI system or its training data.
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