50 citations · 149 across the 15 of their papers we have counts for
5 papers · 1 filter
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?
Rui Wen, Michael Backes, Yang Zhang
Machine learning has revolutionized numerous domains, playing a crucial role in driving advancements and enabling data-centric processes. The significance of data in training model…
Membership Inference Attacks Against In-Context Learning
Rui Wen, Zheng Li, Michael Backes +1
Adapting Large Language Models (LLMs) to specific tasks introduces concerns about computational efficiency, prompting an exploration of efficient methods such as In-Context Learnin…
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka +18
Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study…
Efficient Data-Free Model Stealing with Label Diversity
Yiyong Liu, Rui Wen, Michael Backes +1
Machine learning as a Service (MLaaS) allows users to query the machine learning model in an API manner, which provides an opportunity for users to enjoy the benefits brought by th…
Instruction Backdoor Attacks Against Customized LLMs
Rui Zhang, Hongwei Li, Rui Wen +5
The increasing demand for customized Large Language Models (LLMs) has led to the development of solutions like GPTs. These solutions facilitate tailored LLM creation via natural la…