7 citations · 15 across the 11 of their papers we have counts for
12 papers
Understanding the Stealthy BGP Hijacking Risk in the ROV Era
Yihao Chen, Qi Li, Ke Xu +2
The partial deployment of Route Origin Validation (ROV) poses an unexpected security threat known as stealthy BGP hijacking, i.e., a particularly elusive form of BGP hijacking wher…
A Hard-Label Black-Box Evasion Attack against ML-based Malicious Traffic Detection Systems
Zixuan Liu, Yi Zhao, Zhuotao Liu +4
Machine Learning (ML)-based malicious traffic detection is a promising security paradigm. It outperforms rule-based traditional detection by identifying various advanced attacks. H…
SafeSearch: Automated Red-Teaming of LLM-Based Search Agents
Jianshuo Dong, Sheng Guo, Hao Wang +6
Search agents connect LLMs to the Internet, enabling them to access broader and more up-to-date information. However, this also introduces a new threat surface: unreliable search r…
Pegasus: A Universal Framework for Scalable Deep Learning Inference on the Dataplane
Yinchao Zhang, Su Yao, Yong Feng +9
The paradigm of Intelligent DataPlane (IDP) embeds deep learning (DL) models on the network dataplane to enable intelligent traffic analysis at line-speed. However, the current use…
Towards Robust Multi-tab Website Fingerprinting
Xinhao Deng, Xiyuan Zhao, Qilei Yin +5
Website fingerprinting enables an eavesdropper to determine which websites a user is visiting over an encrypted connection. State-of-the-art website fingerprinting (WF) attacks hav…
Towards Fine-Grained Webpage Fingerprinting at Scale
Xiyuan Zhao, Xinhao Deng, Qi Li +4
Website Fingerprinting (WF) attacks can effectively identify the websites visited by Tor clients via analyzing encrypted traffic patterns. Existing attacks focus on identifying dif…
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption
Xuanqi Liu, Zhuotao Liu, Qi Li +2
The escalating focus on data privacy poses significant challenges for collaborative neural network training, where data ownership and model training/deployment responsibilities res…
Brain-on-Switch: Towards Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis at Line-Speed
Jinzhu Yan, Haotian Xu, Zhuotao Liu +4
The emerging programmable networks sparked significant research on Intelligent Network Data Plane (INDP), which achieves learning-based traffic analysis at line-speed. Prior art in…
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach
Qi Tan, Qi Li, Yi Zhao +3
Federated Learning (FL) trains a black-box and high-dimensional model among different clients by exchanging parameters instead of direct data sharing, which mitigates the privacy l…
Learning with Semantics: Towards a Semantics-Aware Routing Anomaly Detection System
Yihao Chen, Qilei Yin, Qi Li +6
BGP is the de facto inter-domain routing protocol to ensure global connectivity of the Internet. However, various reasons, such as deliberate attacks or misconfigurations, could ca…
LLMs Can Understand Encrypted Prompt: Towards Privacy-Computing Friendly Transformers
Xuanqi Liu, Zhuotao Liu
The community explored to build private inference frameworks for transformer-based large language models (LLMs) in a server-client setting, where the server holds the model paramet…
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks
Jiaming Mu, Binghui Wang, Qi Li +3
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in various graph structure related tasks such as node classification and graph classification. However, GNNs…