[PDF][PDF] BAIT: Large Language Model Backdoor Scanning by Inverting Attack Target
Recent literature has shown that LLMs are vulnerable to backdoor attacks, where malicious
attackers inject a secret token sequence (ie, trigger) into training prompts and enforce their …
attackers inject a secret token sequence (ie, trigger) into training prompts and enforce their …
UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening
S Cheng, G Shen, K Zhang, G Tao, S An, H Guo… - … on Computer Vision, 2024 - Springer
Deep neural networks (DNNs) have demonstrated effectiveness in various fields. However,
DNNs are vulnerable to backdoor attacks, which inject a unique pattern, called trigger, into …
DNNs are vulnerable to backdoor attacks, which inject a unique pattern, called trigger, into …
[PDF][PDF] Exploring the Orthogonality and Linearity of Backdoor Attacks
Backdoor attacks embed an attacker-chosen pattern into inputs to cause model
misclassification. This security threat to machine learning has been a long concern. There …
misclassification. This security threat to machine learning has been a long concern. There …
DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans
Federated Learning (FL) is commonly used to collaboratively train models with privacy
preservation. In this paper, we found out that the popular diffusion models have introduced a …
preservation. In this paper, we found out that the popular diffusion models have introduced a …