%0 Generic
%A Qiao, Yanqi
%A Liu, Dazhuang
%D 2025
%T Code for the publication "Low-Frequency Black-Box Backdoor Attack via Evolutionary Algorithm"
%U 
%R 10.4121/1753c8aa-adf4-4256-ae74-02e34ba120cf.v1
%K backdoor attack
%K computer vision
%K black-box
%K frequency domain
%K simulated annealing
%K robustness
%X <p>This research aims to investigate the vulnerabilities of existing convolutional neural networks (CNNs) and vision transformers (ViTs) against backdoor attacks and to develop a novel backdooring approach. The study focuses on advancing a new technology in this area. The research uses textual data, with all data (i.e., source code) being independently developed.</p>
%I 4TU.ResearchData