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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 491–500 of 523 papers

Title	Date	Tasks	Status	Hype
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks	Oct 30, 2020	Backdoor AttackBIG-bench Machine Learning	—Unverified	0
Backdoor Attack against Speaker Verification	Oct 22, 2020	Backdoor AttackClustering	CodeCode Available	1
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers	Oct 16, 2020	Backdoor AttackBIG-bench Machine Learning	CodeCode Available	1
Input-Aware Dynamic Backdoor Attack	Oct 16, 2020	Backdoor AttackDiversity	CodeCode Available	1
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks	Oct 7, 2020	Backdoor Attack	—Unverified	0
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models	Oct 6, 2020	Backdoor AttackBIG-bench Machine Learning	—Unverified	0
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems	Sep 15, 2020	Backdoor AttackFace Recognition	—Unverified	0
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases	Jul 31, 2020	Backdoor Attack	CodeCode Available	1
Backdoor Learning: A Survey	Jul 17, 2020	Adversarial AttackBackdoor Attack	CodeCode Available	2
Deep Learning Backdoors	Jul 16, 2020	Backdoor AttackDeep Learning	—Unverified	0

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