Technical Program

Paper Detail

Paper IDB-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
TimeThursday, 10 December, 17:30 - 19:30
Presentation Time:Thursday, 10 December, 18:00 - 18:15 Check your Time Zone
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.