In order to prevent illegal or unauthorized access of image data such as human faces and ensure legitimate users can use authorization-protected data, reversible adversarial attack technique is rise. Reversible adversarial examples (RAE) get both attack capability and reversibility at the same time. However, the existing technique can not meet application requirements because of serious distortion and failure of image recovery when adversarial perturbations get strong. In this paper, we take advantage of Reversible Image Transformation technique to generate RAE and achieve reversible adversarial attack. Experimental results show that proposed RAE generation scheme can ensure imperceptible image distortion and the original image can be reconstructed error-free. What's more, both the attack ability and the image quality are not limited by the perturbation amplitude.

翻译：为了防止非法或未经授权获取图像数据,例如人的脸部,并确保合法用户能够使用授权保护的数据,可逆对抗攻击技术正在上升。可逆对抗性攻击技术(RAE)同时获得攻击能力,同时获得可逆性;然而,由于在对抗性干扰加剧时,图像恢复严重扭曲和失败,现有技术无法满足应用要求。在本文中,我们利用可逆形象变换技术生成RAE,实现可逆对抗性攻击。实验结果显示,拟议的RAE生成方案可以确保无法察觉的图像扭曲,原始图像可以重建,没有错误。此外,攻击能力和图像质量不受扰动振动振动音限制。