SOTAVerified

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 151–175 of 523 papers

TitleStatusHype
GENIE: Watermarking Graph Neural Networks for Link Prediction—0
Generalization Bound and New Algorithm for Clean-Label Backdoor AttackCode0
Invisible Backdoor Attacks on Diffusion ModelsCode1
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents—0
DiffPhysBA: Diffusion-based Physical Backdoor Attack against Person Re-Identification in Real-World—0
Cross-Context Backdoor Attacks against Graph Prompt LearningCode0
Towards Unified Robustness Against Both Backdoor and Adversarial AttacksCode0
Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew ResilienceCode1
TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation ModelsCode0
Partial train and isolate, mitigate backdoor attack—0
Mitigating Backdoor Attack by Injecting Proactive Defensive BackdoorCode0
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee—0
Are You Copying My Prompt? Protecting the Copyright of Vision Prompt for VPaaS via Watermark—0
Towards Imperceptible Backdoor Attack in Self-supervised LearningCode1
TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language ModelsCode0
EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding InspectionCode0
An Invisible Backdoor Attack Based On Semantic Feature—0
Rethinking Graph Backdoor Attacks: A Distribution-Preserving PerspectiveCode1
Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision TransformersCode1
Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning—0
Poisoning-based Backdoor Attacks for Arbitrary Target Label with Positive Triggers—0
Towards Robust Physical-world Backdoor Attacks on Lane Detection—0
BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection—0
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning—0
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated LearningCode1
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