16 citations · 20 across the 6 of their papers we have counts for
6 papers
Whispers of Data: Unveiling Label Distributions in Federated Learning Through Virtual Client Simulation
Zhixuan Ma, Haichang Gao, Junxiang Huang +1
Federated Learning enables collaborative training of a global model across multiple geographically dispersed clients without the need for data sharing. However, it is susceptible t…
GlitchMiner: Mining Glitch Tokens in Large Language Models via Gradient-based Discrete Optimization
Zihui Wu, Haichang Gao, Ping Wang +3
Glitch tokens, inputs that trigger unpredictable or anomalous behavior in Large Language Models (LLMs), pose significant challenges to model reliability and safety. Existing detect…
The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models
Zihui Wu, Haichang Gao, Jianping He +1
Large language models (LLMs) have demonstrated remarkable capabilities, but their power comes with significant security considerations. While extensive research has been conducted…
SoK: Acoustic Side Channels
Ping Wang, Shishir Nagaraja, Aurélien Bourquard +2
We provide a state-of-the-art analysis of acoustic side channels, cover all the significant academic research in the area, discuss their security implications and countermeasures,…
AdvFunMatch: When Consistent Teaching Meets Adversarial Robustness
Zihui Wu, Haichang Gao, Bingqian Zhou +1
\emph{Consistent teaching} is an effective paradigm for implementing knowledge distillation (KD), where both student and teacher models receive identical inputs, and KD is treated…
Towards Strengthening Deep Learning-based Side Channel Attacks with Mixup
Zhimin Luo, Mengce Zheng, Ping Wang +3
In recent years, various deep learning techniques have been exploited in side channel attacks, with the anticipation of obtaining more appreciable attack results. Most of them conc…