4 papers
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…
PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming
Liming Liu, Jiangkai Wu, Haoyang Wang +3
Traditional video compression algorithms exhibit significant quality degradation at extremely low bitrates. Promptus emerges as a new paradigm for video streaming, substantially cu…
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…
Large Language Models for Networking: Workflow, Advances and Challenges
Chang Liu, Xiaohui Xie, Xinggong Zhang +1
The networking field is characterized by its high complexity and rapid iteration, requiring extensive expertise to accomplish network tasks, ranging from network design, configurat…