| Title | RDP-WGAN: Image Data Privacy Protection Based on Rényi Differential Privacy |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Ma, Xuebin, Yang, Ren, Zheng, Maobo |
| Conference Name | 2022 18th International Conference on Mobility, Sensing and Networking (MSN) |
| Keywords | composability, Data models, Differential privacy, generative adversarial networks, Human Behavior, image data privacy protection, Industries, privacy, pubcrawl, Rényi differential privacy, resilience, Resiliency, Scalability, Sensors, Training |
| Abstract | In recent years, artificial intelligence technology based on image data has been widely used in various industries. Rational analysis and mining of image data can not only promote the development of the technology field but also become a new engine to drive economic development. However, the privacy leakage problem has become more and more serious. To solve the privacy leakage problem of image data, this paper proposes the RDP-WGAN privacy protection framework, which deploys the Renyi differential privacy (RDP) protection techniques in the training process of generative adversarial networks to obtain a generative model with differential privacy. This generative model is used to generate an unlimited number of synthetic datasets to complete various data analysis tasks instead of sensitive datasets. Experimental results demonstrate that the RDP-WGAN privacy protection framework provides privacy protection for sensitive image datasets while ensuring the usefulness of the synthetic datasets. |
| DOI | 10.1109/MSN57253.2022.00060 |
| Citation Key | ma_rdp-wgan_2022 |
RDP-WGAN: Image Data Privacy Protection Based on Rényi Differential Privacy