Adversarial catoptric light: An effective, stealthy and robust physical‐world attack to DNNs
Adversarial catoptric light: An effective, stealthy and robust physical‐world attack to DNNs
Abstract Recent studies have demonstrated that finely tuned deep neural networks (DNNs) are susceptible to adversarial attacks. Conventional physical attacks employ stickers as perturbations, achieving robust adversarial effects but compromising stealthiness. Recent innovations utilise light beams, such as lasers and projectors, for perturbation generation, allowing for stealthy physical attacks at …