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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

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Showing 451–475 of 523 papers

TitleStatusHype
Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy BreachesCode0
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers—0
False Memory Formation in Continual Learners Through Imperceptible Backdoor Trigger—0
Imperceptible and Multi-channel Backdoor Attack against Deep Neural Networks—0
Backdoors Stuck At The Frontdoor: Multi-Agent Backdoor Attacks That Backfire—0
Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World—0
Neighboring Backdoor Attacks on Graph Convolutional Network—0
Defending against Backdoor Attacks in Natural Language Generation—0
Rethink the Evaluation for Attack Strength of Backdoor Attacks in Natural Language Processing—0
Compression-Resistant Backdoor Attack against Deep Neural Networks—0
DEFEAT: Deep Hidden Feature Backdoor Attacks by Imperceptible Perturbation and Latent Representation Constraints—0
Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks—0
Backdoor Attack with Imperceptible Input and Latent Modification—0
Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated LearningCode0
Backdoor Attack through Frequency DomainCode0
DBIA: Data-free Backdoor Injection Attack against Transformer NetworksCode0
An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences—0
Enhancing Backdoor Attacks with Multi-Level MMD RegularizationCode0
Backdoor Pre-trained Models Can Transfer to AllCode0
Widen The Backdoor To Let More Attackers In—0
Dyn-Backdoor: Backdoor Attack on Dynamic Link Prediction—0
BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models—0
MARNET: Backdoor Attacks against Value-Decomposition Multi-Agent Reinforcement Learning—0
Defending Backdoor Data Poisoning Attacks by Using Noisy Label Defense Algorithm—0
Gradient Broadcast Adaptation: Defending against the backdoor attack in pre-trained models—0
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