Research on security dissemination method of facial images based on differential privacy
He Chunlu1，Tang Qi2
1. National Science Library， Chinese Academy of Sciences; 2. Hunan University
Abstract： Face data contains rich identity information, and its privacy leakage has attracted much attention. Traditional differential privacy methods directly add noise to pixels or feature vectors as a whole, resulting in decreased recognition performance and lack of interpretability. Therefore, this paper proposes a new differential privacy method, which combines the feature embedding vector with the classification method design, and innovatively converts the response data into two forms of radial radius and tangential angle, so as to better adapt the angle and distance measurement in classification. On this basis, a differential privacy noise generation mechanism based on angle and radius is constructed, and the privacy budget is defined and mathematically proved by the differential privacy combination theorem. In addition, this paper designs a privacy image generation method to achieve a balance between privacy and availability by optimizing the evaluation function. The experimental results based on three public datasets show that the proposed method performs well in the combined application of radial and tangential directions, and significantly improves the recognition performance under the same privacy budget. This method achieves both privacy protection and classification availability, and shows significant advantages in interpretability and performance.
Key words : differential privacy; face recognition; feature embedding; privacy-preserve
