15 citations · 32 across the 5 of their papers we have counts for
5 papers
LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets
Shixin Guo, Ming Zhong, Xuhong Zhang +5
Generating high-quality adversarial texts with low query budgets remains a challenging problem in the hard-label scenario. Most existing approaches rely on greedy algorithms, where…
G-Fuzz: A Directed Fuzzing Framework for gVisor
Yuwei Li, Yuan Chen, Shouling Ji +6
gVisor is a Google-published application-level kernel for containers. As gVisor is lightweight and has sound isolation, it has been widely used in many IT enterprises \cite{Stripe,…
FreeEagle: Detecting Complex Neural Trojans in Data-Free Cases
Chong Fu, Xuhong Zhang, Shouling Ji +4
Trojan attack on deep neural networks, also known as backdoor attack, is a typical threat to artificial intelligence. A trojaned neural network behaves normally with clean inputs.…
TextDefense: Adversarial Text Detection based on Word Importance Entropy
Lujia Shen, Xuhong Zhang, Shouling Ji +4
Currently, natural language processing (NLP) models are wildly used in various scenarios. However, NLP models, like all deep models, are vulnerable to adversarially generated text.…
Hijack Vertical Federated Learning Models As One Party
Pengyu Qiu, Xuhong Zhang, Shouling Ji +4
Vertical federated learning (VFL) is an emerging paradigm that enables collaborators to build machine learning models together in a distributed fashion. In general, these parties h…