4 papers
Universal Perturbation-based Secret Key-Controlled Data Hiding
Donghua Wang, Wen Yao, Tingsong Jiang +1
Deep neural networks (DNNs) are demonstrated to be vulnerable to universal perturbation, a single quasi-perceptible perturbation that can deceive the DNN on most images. However, t…
Multi-objective Evolutionary Search of Variable-length Composite Semantic Perturbations
Jialiang Sun, Wen Yao, Tingsong Jiang +1
Deep neural networks have proven to be vulnerable to adversarial attacks in the form of adding specific perturbations on images to make wrong outputs. Designing stronger adversaria…
A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications
Donghua Wang, Wen Yao, Tingsong Jiang +3
Wide deployment of deep neural networks (DNNs) based applications (e.g., style transfer, cartoonish), stimulating the requirement of copyright protection of such application's prod…
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design
Jialiang Sun, Wen Yao, Tingsong Jiang +1
The phenomenon of adversarial examples has been revealed in variant scenarios. Recent studies show that well-designed adversarial defense strategies can improve the robustness of d…