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Backdoor Attack

Backdoor attacks inject maliciously constructed data into a training set so that, at test time, the trained model misclassifies inputs patched with a backdoor trigger as an adversarially-desired target class.

Papers

Showing 4150 of 523 papers

TitleStatusHype
You Can Backdoor Personalized Federated LearningCode1
Risk-optimized Outlier Removal for Robust 3D Point Cloud ClassificationCode1
Towards Stealthy Backdoor Attacks against Speech Recognition via Elements of SoundCode1
FedDefender: Backdoor Attack Defense in Federated LearningCode1
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural NetworkCode1
VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion ModelsCode1
Backdoor Attack with Sparse and Invisible TriggerCode1
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data PoisoningCode1
UNICORN: A Unified Backdoor Trigger Inversion FrameworkCode1
Influencer Backdoor Attack on Semantic SegmentationCode1
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