Privacy protection method, system and equipment based on machine learning and medium

The invention discloses a privacy protection method, system and device based on machine learning and a medium, and the method comprises the steps: inputting differential privacy noise into an unscented Kalman filter for filtering processing, and determining filtered noise; inputting the filtered noise into a machine learning model for training processing, and determining an output model; performing practicability evaluation processing and privacy evaluation processing on the output model, and determining a model evaluation result; adjusting the output model according to the model evaluation result, determining a target model and outputting privacy protection data; according to the embodiment, the practicability of the differential privacy machine learning model can be improved, and the method can be widely applied to the technical field of data protection. 本发明公开了一种基于机器学习的隐私保护方法、系统、设备及介质，其中，方法包括：将差分隐私噪声输入无味卡尔曼滤波器进行过滤处理，确定过滤噪声；将所述过滤噪声输入机器学习模型进行训练处理，确定输出模型；对所述输出模型进行实用性评估处理和隐私性评估处理，确定模型评估结果；根据所述模型评估结果对所述输出模型进行调整，