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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 331–340 of 523 papers

TitleStatusHype
An Effective and Resilient Backdoor Attack Framework against Deep Neural Networks and Vision Transformers—0
An Invisible Backdoor Attack Based On Semantic Feature—0
An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences—0
Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning—0
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks—0
Are You Copying My Prompt? Protecting the Copyright of Vision Prompt for VPaaS via Watermark—0
A Robust Attack: Displacement Backdoor Attack—0
A Semantic and Clean-label Backdoor Attack against Graph Convolutional Networks—0
A semantic backdoor attack against Graph Convolutional Networks—0
AS-FIBA: Adaptive Selective Frequency-Injection for Backdoor Attack on Deep Face Restoration—0
Show:102550
← PrevPage 34 of 53Next →

No leaderboard results yet.