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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 61–70 of 523 papers

Title	Date	Tasks	Status	Hype	Score
BadPrompt: Backdoor Attacks on Continuous Prompts	Nov 27, 2022	Backdoor AttackPrompt Learning	CodeCode Available	1	5
CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive Learning	Nov 15, 2022	Backdoor AttackContrastive Learning	CodeCode Available	1	5
Defending against Backdoors in Federated Learning with Robust Learning Rate	Jul 7, 2020	Backdoor AttackFederated Learning	CodeCode Available	1	5
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers	Oct 16, 2020	Backdoor AttackBIG-bench Machine Learning	CodeCode Available	1	5
Backdoor Attacks for Remote Sensing Data with Wavelet Transform	Nov 15, 2022	Backdoor Attackbackdoor defense	CodeCode Available	1	5
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification	Dec 21, 2020	Adversarial AttackBackdoor Attack	CodeCode Available	1	5
Anti-Backdoor Learning: Training Clean Models on Poisoned Data	Oct 22, 2021	Backdoor Attack	CodeCode Available	1	5
Backdoor Attacks Against Dataset Distillation	Jan 3, 2023	Backdoor AttackDataset Distillation	CodeCode Available	1	5
Anti-Distillation Backdoor Attacks: Backdoors Can Really Survive in Knowledge Distillation	Oct 24, 2021	Backdoor AttackKnowledge Distillation	CodeCode Available	1	5
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning	Oct 23, 2022	Backdoor Attackbackdoor defense	CodeCode Available	1	5

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