7 citations · 14 across the 4 of their papers we have counts for
4 papers
Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning
Hongbin Liu, Wenjie Qu, Jinyuan Jia +1
Classifiers in supervised learning have various security and privacy issues, e.g., 1) data poisoning attacks, backdoor attacks, and adversarial examples on the security side as wel…
MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples
Jinyuan Jia, Wenjie Qu, Neil Zhenqiang Gong
Multi-label classification, which predicts a set of labels for an input, has many applications. However, multiple recent studies showed that multi-label classification is vulnerabl…
jTrans: Jump-Aware Transformer for Binary Code Similarity
Hao Wang, Wenjie Qu, Gilad Katz +5
Binary code similarity detection (BCSD) has important applications in various fields such as vulnerability detection, software component analysis, and reverse engineering. Recent s…
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning
Hongbin Liu, Jinyuan Jia, Wenjie Qu +1
Given a set of unlabeled images or (image, text) pairs, contrastive learning aims to pre-train an image encoder that can be used as a feature extractor for many downstream tasks. I…