Paper ID | B-3-3.3 |
Paper Title |
VISUAL SECURITY EVALUATION OF LEARNABLE IMAGE ENCRYPTION METHODS AGAINST CIPHERTEXT-ONLY ATTACKS |
Authors |
Warit Sirichotedumrong, Hitoshi Kiya, Tokyo Metropolitan University, Japan |
Session |
B-3-3: Recent Advances in Multimedia Security and Forensics |
Time | Thursday, 10 December, 17:30 - 19:30 |
Presentation Time: | Thursday, 10 December, 18:00 - 18:15 Check your Time Zone |
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All times are in New Zealand Time (UTC +13) |
Topic |
Multimedia Security and Forensics (MSF): |
Abstract |
Various visual information protection methods have been proposed for privacy-preserving deep neural networks (DNNs). In contrast, attack methods on such protection methods have been studied simultaneously. In this paper, we evaluate state-of-the-art visual protection methods for privacy-preserving DNNs in terms of visual security against ciphertext-only attacks (COAs). We focus on brute-force attack, feature reconstruction attack (FR-Attack), inverse transformation attack (ITN-Attack), and GAN-based attack (GAN-Attack), which have been proposed to reconstruct visual information on plain images from the visually-protected images. The detail of various attack is first summarized, and then visual security of the protection methods is evaluated. Experimental results demonstrate that most of protection methods, including pixel-wise encryption, have not enough robustness against GAN-Attack, while a few protection methods are robust enough against GAN-Attack. |