<ul><li>Unlearnable data (ULD) is a defense technique to prevent machine learning models from learning meaningful patterns from specific data, protecting data privacy and security.</li><li>This survey provides a comprehensive review of ULD, including data generation methods, evaluation metrics, and practical applications.</li><li>Different ULD approaches are compared and contrasted in terms of unlearnability, imperceptibility, efficiency, and robustness.</li><li>The survey also explores challenges and future research directions to enhance the effectiveness and applicability of ULD in data protection for machine learning.</li></ul>

A Survey on Unlearnable Data

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