4 papers
ImF: Implicit Fingerprint for Large Language Models
Jiaxuan Wu, Wanli Peng, Hang Fu +2
Training large language models (LLMs) is resource-intensive and expensive, making protecting intellectual property (IP) for LLMs crucial. Recently, embedding fingerprints into LLMs…
Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Wanli Peng, Xin Chen, Hang Fu +3
Recent advances in large language models (LLMs) have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference abil…
BadApex: Backdoor Attack Based on Adaptive Optimization Mechanism of Black-box Large Language Models
Zhengxian Wu, Juan Wen, Wanli Peng +3
Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned a…
Generative Text Steganography with Large Language Model
Jiaxuan Wu, Zhengxian Wu, Yiming Xue +2
Recent advances in large language models (LLMs) have blurred the boundary of high-quality text generation between humans and machines, which is favorable for generative text stegan…