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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 391–400 of 523 papers

TitleStatusHype
Backdoor Attacks in Peer-to-Peer Federated Learning—0
Universal Detection of Backdoor Attacks via Density-based Clustering and Centroids AnalysisCode0
You Are Catching My Attention: Are Vision Transformers Bad Learners Under Backdoor Attacks?—0
Color Backdoor: A Robust Poisoning Attack in Color SpaceCode0
SSDA: Secure Source-Free Domain AdaptationCode0
Mind Your Heart: Stealthy Backdoor Attack on Dynamic Deep Neural Network in Edge ComputingCode0
Vulnerabilities of Deep Learning-Driven Semantic Communications to Backdoor (Trojan) Attacks—0
VSVC: Backdoor attack against Keyword Spotting based on Voiceprint Selection and Voice Conversion—0
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends—0
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
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