SOTAVerified

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

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Showing 71–80 of 523 papers

TitleStatusHype
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised LearningCode1
FlowMur: A Stealthy and Practical Audio Backdoor Attack with Limited KnowledgeCode1
FedDefender: Backdoor Attack Defense in Federated LearningCode1
Backdoor Attacks for Remote Sensing Data with Wavelet TransformCode1
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated LearningCode1
BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive LearningCode1
Backdoor Attacks on Crowd CountingCode1
BadEdit: Backdooring large language models by model editingCode1
Backdoor Attacks on Federated Learning with Lottery Ticket HypothesisCode1
Imperceptible and Robust Backdoor Attack in 3D Point CloudCode1
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