3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
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…
Large Language Models powered Malicious Traffic Detection: Architecture, Opportunities and Case Study
Xinggong Zhang, Haotian Meng, Qingyang Li +2
Malicious traffic detection is a pivotal technology for network security to identify abnormal network traffic and detect network attacks. Large Language Models (LLMs) are trained o…
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…