7 citations · 24 across the 10 of their papers we have counts for
11 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…
LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks
Yongjie Xu, Guangke Chen, Fu Song +1
Backdoor attacks embed hidden associations between triggers and targets in deep neural networks (DNNs), causing them to predict the target when a trigger is present while maintaini…
SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Covers
Guangke Chen, Yedi Zhang, Fu Song +3
Singing voice conversion (SVC) automates song covers by converting a source singing voice from a source singer into a new singing voice with the same lyrics and melody as the sourc…
SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems
Guangke Chen, Yedi Zhang, Fu Song
Membership inference attacks allow adversaries to determine whether a particular example was contained in the model's training dataset. While previous works have confirmed the feas…
QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems
Guangke Chen, Yedi Zhang, Zhe Zhao +1
Current adversarial attacks against speaker recognition systems (SRSs) require either white-box access or heavy black-box queries to the target SRS, thus still falling behind pract…
Towards Understanding and Mitigating Audio Adversarial Examples for Speaker Recognition
Guangke Chen, Zhe Zhao, Fu Song +4
Speaker recognition systems (SRSs) have recently been shown to be vulnerable to adversarial attacks, raising significant security concerns. In this work, we systematically investig…
AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker Recognition Systems
Guangke Chen, Zhe Zhao, Fu Song +3
Recent work has illuminated the vulnerability of speaker recognition systems (SRSs) against adversarial attacks, raising significant security concerns in deploying SRSs. However, t…
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…
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems
Guangke Chen, Sen Chen, Lingling Fan +4
Speaker recognition (SR) is widely used in our daily life as a biometric authentication or identification mechanism. The popularity of SR brings in serious security concerns, as de…