  Quantum computing has been widely applied in various fields, such as quantum
physics simulations, quantum machine learning, and big data analysis. However,
in the domains of data-driven paradigm, how to ensure the privacy of the
database is becoming a vital problem. For classical computing, we can
incorporate the concept of differential privacy (DP) to meet the standard of
privacy preservation by manually adding the noise. In the quantum computing
scenario, researchers have extended classic DP to quantum differential privacy
(QDP) by considering the quantum noise. In this paper, we propose a novel
approach to satisfy the QDP definition by considering the errors generated by
the projection operator measurement, which is denoted as shot noises. Then, we
discuss the amount of privacy budget that can be achieved with shot noises,
which serves as a metric for the level of privacy protection. Furthermore, we
provide the QDP of shot noise in quantum circuits with depolarizing noise.
Through numerical simulations, we show that shot noise can effectively provide
privacy protection in quantum computing.
