Abstract: With the rapid progress of artificial intelligence and computer vision technology,facial information has been widely used in smart security,financial payment,and social media,etc.Once the collected facial information is leaked or illegally sold by unscrupulous individuals,it will cause adverse consequences.Therefore,how to prevent the original facial database from being illegally accessed and trained by malicious parties,and how to prevent illegal recognition,is an urgent issue that needs to be solved.Therefore,a reversible facial privacy protection method based on “invisible mask” is proposed.If the adversarial facial image is illegally accessed,it will cause the unauthorized facial recognition system to incorrectly recognize,and for authorized users,the original facial information can be recovered by removing the “invisible mask”,ensuring that the authorized facial recognition system can correctly recognize,thus achieving the purpose of protecting the facial database.Experimental results show that the method generates adversarial facial images with higher visual quality,the average PSNR between the adversarial facial image and the original facial image without attack layer can reach 55 dB,and the false recognition rate of the unauthorized system can reach 99.6%.At the same time,the method realizes reversible recovery of facial images,the average PSNR of the recovered facial image is 61 dB,and the correct recognition rate of the authorized system can reach 99.8%.Therefore,the proposed method can effectively protect the facial database.

Key words: Deep learning, Invisible masks, Adversarial examples, Facial dataset protection, Visual transformation, Reversible facial privacy protection