Differential privacy is a concept designed to prevent the leakage of private information in statistical inference, and it has recently been extended to quantum systems as quantum differential privacy. This talk address differential privacy, quantum differential privacy, and quantum advantage in private statistical inference. Among various types of statistical inference, this talk especially focus on private hypothesis testing, and introduce a result showing that by employing a new quantum privacy mechanism involving a SIC-POVM, one can achieve a privacy-utility trade-off that is unattainable in the classical setting.

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