  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.
