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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 351–375 of 523 papers

TitleStatusHype
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
Attack On Prompt: Backdoor Attack in Prompt-Based Continual Learning—0
Backdoor Attack in the Physical World—0
Backdoor Attack on Multilingual Machine Translation—0
Backdoor Attack on Vertical Federated Graph Neural Network Learning—0
Backdoor Attack on Vision Language Models with Stealthy Semantic Manipulation—0
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger—0
Backdoor Attacks against Image-to-Image Networks—0
Backdoor Attacks Against Incremental Learners: An Empirical Evaluation Study—0
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions—0
Backdoor Attacks in Peer-to-Peer Federated Learning—0
Backdoor Attacks on Bayesian Neural Networks using Reverse Distribution—0
Backdoor Attacks on the DNN Interpretation System—0
Backdoor Attacks with Input-unique Triggers in NLP—0
Exploiting Machine Unlearning for Backdoor Attacks in Deep Learning System—0
Backdoor Attack with Imperceptible Input and Latent Modification—0
Backdoor Attack with Mode Mixture Latent Modification—0
BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning—0
BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning—0
BackdoorBench: A Comprehensive Benchmark of Backdoor Learning—0
Backdoor Detection through Replicated Execution of Outsourced Training—0
Backdoored Retrievers for Prompt Injection Attacks on Retrieval Augmented Generation of Large Language Models—0
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers—0
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations—0
Backdooring Outlier Detection Methods: A Novel Attack Approach—0
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