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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 451–500 of 523 papers

TitleStatusHype
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain—0
Backdoor Attack and Defense for Deep Regression—0
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 Triggers—0
Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting—0
BadNL: Backdoor Attacks Against NLP Models—0
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from ScratchCode1
Handcrafted Backdoors in Deep Neural Networks—0
Defending Against Backdoor Attacks in Natural Language GenerationCode1
Detecting Backdoor in Deep Neural Networks via Intentional Adversarial Perturbations—0
Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic TriggerCode1
Backdoor Attacks on Self-Supervised LearningCode1
Poisoning MorphNet for Clean-Label Backdoor Attack to Point Clouds—0
BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning—0
A Master Key Backdoor for Universal Impersonation Attack against DNN-based Face Verification—0
Stealthy Backdoors as Compression ArtifactsCode0
Robust Backdoor Attacks against Deep Neural Networks in Real Physical World—0
Explainability-based Backdoor Attacks Against Graph Neural Networks—0
Backdoor Attack in the Physical World—0
PointBA: Towards Backdoor Attacks in 3D Point Cloud—0
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 Symmetry—0
Hidden Backdoor Attack against Semantic Segmentation Models—0
Targeted Attack against Deep Neural Networks via Flipping Limited Weight BitsCode1
WaNet -- Imperceptible Warping-based Backdoor AttackCode1
Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models—0
DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection—0
Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-Level Backdoor AttacksCode1
CLEAR: Clean-Up Sample-Targeted Backdoor in Neural Networks—0
LIRA: Learnable, Imperceptible and Robust Backdoor AttacksCode1
WaNet - Imperceptible Warping-based Backdoor AttackCode1
BAAAN: Backdoor Attacks Against Auto-encoder and GAN-Based Machine Learning Models—0
Deep Feature Space Trojan Attack of Neural Networks by Controlled DetoxificationCode1
HaS-Nets: A Heal and Select Mechanism to Defend DNNs Against Backdoor Attacks for Data Collection Scenarios—0
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation—0
Backdoor Attacks on the DNN Interpretation System—0
ONION: A Simple and Effective Defense Against Textual Backdoor AttacksCode1
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks—0
Backdoor Attack against Speaker VerificationCode1
Embedding and Extraction of Knowledge in Tree Ensemble ClassifiersCode1
Input-Aware Dynamic Backdoor AttackCode1
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks—0
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models—0
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems—0
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free CasesCode1
Backdoor Learning: A SurveyCode2
Deep Learning Backdoors—0
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