3 citations · 3 across the 3 of their papers we have counts for
4 papers
Tanchun: Robust Flow-Based HTTP(S) DDoS Detection via Behavioral Attribute Guidance
Qingyang Li, Yunpeng Tan, Mingxin Yang +5
HTTP(S) DDoS attacks have surged in frequency and scale, posing a significant threat to network security. Flow-based detection is a promising solution for large-scale HTTP(S) DDoS…
MalMoE: Mixture-of-Experts Enhanced Encrypted Malicious Traffic Detection Under Graph Drift
Yunpeng Tan, Qingyang Li, Mingxin Yang +3
Encryption has been commonly used in network traffic to secure transmission, but it also brings challenges for malicious traffic detection, due to the invisibility of the packet pa…
MCBlock: Boosting Neural Radiance Field Training Speed by MCTS-based Dynamic-Resolution Ray Sampling
Yunpeng Tan, Junlin Hao, Jiangkai Wu +3
Neural Radiance Field (NeRF) is widely known for high-fidelity novel view synthesis. However, even the state-of-the-art NeRF model, Gaussian Splatting, requires minutes for trainin…
DoLLM: How Large Language Models Understanding Network Flow Data to Detect Carpet Bombing DDoS
Qingyang Li, Yihang Zhang, Zhidong Jia +7
It is an interesting question Can and How Large Language Models (LLMs) understand non-language network data, and help us detect unknown malicious flows. This paper takes Carpet Bom…