6 citations · 10 across the 5 of their papers we have counts for
8 papers
AudioJailbreak: Jailbreak Attacks against End-to-End Large Audio-Language Models
Guangke Chen, Fu Song, Zhe Zhao +7
Jailbreak attacks to Large audio-language models (LALMs) are studied recently, but they exclusively focused on the attack scenario where the adversary can fully manipulate user pro…
Training Verification-Friendly Neural Networks via Neuron Behavior Consistency
Zongxin Liu, Zhe Zhao, Fu Song +4
Formal verification provides critical security assurances for neural networks, yet its practical application suffers from the long verification time. This work introduces a novel m…
Adversarial Attacks on ML Defense Models Competition
Yinpeng Dong, Qi-An Fu, Xiao Yang +25
Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…
SEC4SR: A Security Analysis Platform for Speaker Recognition
Guangke Chen, Zhe Zhao, Fu Song +3
Adversarial attacks have been expanded to speaker recognition (SR). However, existing attacks are often assessed using different SR models, recognition tasks and datasets, and only…
Attack as Defense: Characterizing Adversarial Examples using Robustness
Zhe Zhao, Guangke Chen, Jingyi Wang +3
As a new programming paradigm, deep learning has expanded its application to many real-world problems. At the same time, deep learning based software are found to be vulnerable to…
BDD4BNN: A BDD-based Quantitative Analysis Framework for Binarized Neural Networks
Yedi Zhang, Zhe Zhao, Guangke Chen +2
Verifying and explaining the behavior of neural networks is becoming increasingly important, especially when they are deployed in safety-critical applications. In this paper, we st…