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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 331–340 of 523 papers

TitleStatusHype
GhostEncoder: Stealthy Backdoor Attacks with Dynamic Triggers to Pre-trained Encoders in Self-supervised Learning—0
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade DefenseCode0
Moiré Backdoor Attack (MBA): A Novel Trigger for Pedestrian Detectors in the Physical World—0
Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic ClassificationCode0
Robust Backdoor Attacks on Object Detection in Real World—0
Physical Invisible Backdoor Based on Camera Imaging—0
MASTERKEY: Practical Backdoor Attack Against Speaker Verification Systems—0
Exploiting Machine Unlearning for Backdoor Attacks in Deep Learning System—0
EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events—0
FTA: Stealthy and Adaptive Backdoor Attack with Flexible Triggers on Federated Learning—0
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