20 citations · 84 across the 21 of their papers we have counts for
7 papers · 1 filter
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
Boyang Zhang, Zheng Li, Ziqing Yang +4
While advanced machine learning (ML) models are deployed in numerous real-world applications, previous works demonstrate these models have security and privacy vulnerabilities. Var…
A Comprehensive Study of Privacy Risks in Curriculum Learning
Joann Qiongna Chen, Xinlei He, Zheng Li +2
Training a machine learning model with data following a meaningful order, i.e., from easy to hard, has been proven to be effective in accelerating the training process and achievin…
Generative Watermarking Against Unauthorized Subject-Driven Image Synthesis
Yihan Ma, Zhengyu Zhao, Xinlei He +3
Large text-to-image models have shown remarkable performance in synthesizing high-quality images. In particular, the subject-driven model makes it possible to personalize the image…
FDINet: Protecting against DNN Model Extraction via Feature Distortion Index
Hongwei Yao, Zheng Li, Haiqin Weng +3
Machine Learning as a Service (MLaaS) platforms have gained popularity due to their accessibility, cost-efficiency, scalability, and rapid development capabilities. However, recent…
NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models
Kai Mei, Zheng Li, Zhenting Wang +2
Prompt-based learning is vulnerable to backdoor attacks. Existing backdoor attacks against prompt-based models consider injecting backdoors into the entire embedding layers or word…
Watermarking Diffusion Model
Yugeng Liu, Zheng Li, Michael Backes +2
The availability and accessibility of diffusion models (DMs) have significantly increased in recent years, making them a popular tool for analyzing and predicting the spread of inf…
Backdoor Attacks Against Dataset Distillation
Yugeng Liu, Zheng Li, Michael Backes +2
Dataset distillation has emerged as a prominent technique to improve data efficiency when training machine learning models. It encapsulates the knowledge from a large dataset into…