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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

Showing 451475 of 523 papers

TitleStatusHype
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain0
Backdoor Attack and Defense for Deep Regression0
Excess Capacity and Backdoor PoisoningCode0
Poison Ink: Robust and Invisible Backdoor AttackCode1
Rethinking Stealthiness of Backdoor Attack against NLP ModelsCode1
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised LearningCode1
Can You Hear It? Backdoor Attacks via Ultrasonic Triggers0
Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting0
BadNL: Backdoor Attacks Against NLP Models0
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from ScratchCode1
Handcrafted Backdoors in Deep Neural Networks0
Defending Against Backdoor Attacks in Natural Language GenerationCode1
Detecting Backdoor in Deep Neural Networks via Intentional Adversarial Perturbations0
Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic TriggerCode1
Backdoor Attacks on Self-Supervised LearningCode1
Poisoning MorphNet for Clean-Label Backdoor Attack to Point Clouds0
BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning0
A Master Key Backdoor for Universal Impersonation Attack against DNN-based Face Verification0
Stealthy Backdoors as Compression ArtifactsCode0
Robust Backdoor Attacks against Deep Neural Networks in Real Physical World0
Explainability-based Backdoor Attacks Against Graph Neural Networks0
Backdoor Attack in the Physical World0
PointBA: Towards Backdoor Attacks in 3D Point Cloud0
Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP ModelsCode1
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry0
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