HideSeeker
Suyuan Liu, Lan Zhang, Haikuo Yu, Jiahui Hou, Kaiwen Guo, Xiang‐Yang Li · 2022
Obfuscation technologies have been well established for on-device image privacy protection, including pixelization, blurring, scribbling, sticker-covering, and inpainting. Despite their remarkable resistance to human observation, recent studies find that some of them are vulnerable to attacks by neural network-based recognition methods. In this work, we reveal the risk of privacy re-disclosure post image protection. Given an obfuscation-protected image, the privacy information includes 1) where the obfuscated region is and 2) what the hidden privacy-related objects are. Thus we focus on uncovering categories of privacy-related objects to evaluate the effectiveness of obfuscation technologies. Under severe obfuscation, unfortunately, even powerful object recognition models can hardly infer hidden privacy information.