33 citations · 88 across the 17 of their papers we have counts for
7 papers · 1 filter
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…
QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks
Yedi Zhang, Zhe Zhao, Fu Song +3
Deep learning has become a promising programming paradigm in software development, owing to its surprising performance in solving many challenging tasks. Deep neural networks (DNNs…
CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning
Zhensu Sun, Xiaoning Du, Fu Song +2
Github Copilot, trained on billions of lines of public code, has recently become the buzzword in the computer science research and practice community. Although it is designed to he…
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…
Advanced Evasion Attacks and Mitigations on Practical ML-Based Phishing Website Classifiers
Yusi Lei, Sen Chen, Lingling Fan +2
Machine learning (ML) based approaches have been the mainstream solution for anti-phishing detection. When they are deployed on the client-side, ML-based classifiers are vulnerable…