Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images

• URL: http://arxiv.org/abs/2009.09283v1
• Date: Sat, 19 Sep 2020 19:02:17 GMT
• Title: Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images
• Authors: Kang Liu, Benjamin Tan, Siddharth Garg
• Abstract summary: State-of-the-art approaches use privacy-preserving generative adversarial networks (PP-GANs) to enable reliable facial expression recognition without leaking users' identity. We show that it is possible to hide the sensitive identification data in the sanitized output images of such PP-GANs for later extraction.
• Score: 13.690485523871855
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Unprecedented data collection and sharing have exacerbated privacy concerns and led to increasing interest in privacy-preserving tools that remove sensitive attributes from images while maintaining useful information for other tasks. Currently, state-of-the-art approaches use privacy-preserving generative adversarial networks (PP-GANs) for this purpose, for instance, to enable reliable facial expression recognition without leaking users' identity. However, PP-GANs do not offer formal proofs of privacy and instead rely on experimentally measuring information leakage using classification accuracy on the sensitive attributes of deep learning (DL)-based discriminators. In this work, we question the rigor of such checks by subverting existing privacy-preserving GANs for facial expression recognition. We show that it is possible to hide the sensitive identification data in the sanitized output images of such PP-GANs for later extraction, which can even allow for reconstruction of the entire input images, while satisfying privacy checks. We demonstrate our approach via a PP-GAN-based architecture and provide qualitative and quantitative evaluations using two public datasets. Our experimental results raise fundamental questions about the need for more rigorous privacy checks of PP-GANs, and we provide insights into the social impact of these.

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