Restore the Image, Preserve the Poisoning Signal
TL;DR for operators Publishing images that remain useful to people while making them poor training material for unauthorized models creates an awkward engineering constraint: stronger interference often comes with more visible image degradation. The paper Leveraging Imperfect Restoration for Data Availability Attack1 shows that those two objectives need not move together. Its proposed method deliberately restores some of the visual damage created by an existing convolution-based poisoning technique while leaving enough class-specific structure to continue disrupting learning. ...