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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 401–425 of 523 papers

TitleStatusHype
Be Careful with Rotation: A Uniform Backdoor Pattern for 3D Shape—0
A Survey on Backdoor Attack and Defense in Natural Language Processing—0
Invisible Backdoor Attack with Dynamic Triggers against Person Re-identificationCode0
PBSM: Backdoor attack against Keyword spotting based on pitch boosting and sound masking—0
MSDT: Masked Language Model Scoring Defense in Text DomainCode0
Going In Style: Audio Backdoors Through Stylistic TransformationsCode0
BATT: Backdoor Attack with Transformation-based Triggers—0
Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via MotifsCode0
Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning—0
Backdoor Attack and Defense in Federated Generative Adversarial Network-based Medical Image Synthesis—0
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class—0
Few-shot Backdoor Attacks via Neural Tangent KernelsCode0
Understanding Impacts of Task Similarity on Backdoor Attack and Detection—0
Where to Attack: A Dynamic Locator Model for Backdoor Attack in Text ClassificationsCode0
Defending Against Backdoor Attack on Graph Nerual Network by Explainability—0
FedPrompt: Communication-Efficient and Privacy Preserving Prompt Tuning in Federated Learning—0
Bidirectional Contrastive Split Learning for Visual Question Answering—0
RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNNCode0
Link-Backdoor: Backdoor Attack on Link Prediction via Node InjectionCode0
Confidence Matters: Inspecting Backdoors in Deep Neural Networks via Distribution Transfer—0
A Knowledge Distillation-Based Backdoor Attack in Federated Learning—0
FRIB: Low-poisoning Rate Invisible Backdoor Attack based on Feature Repair—0
Technical Report: Assisting Backdoor Federated Learning with Whole Population Knowledge Alignment—0
Versatile Weight Attack via Flipping Limited BitsCode0
Invisible Backdoor Attacks Using Data Poisoning in the Frequency Domain—0
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