3 citations · 13 across the 11 of their papers we have counts for
9 papers · 1 filter
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…
Promptus: Can Prompts Streaming Replace Video Streaming with Stable Diffusion
Jiangkai Wu, Liming Liu, Yunpeng Tan +2
With the exponential growth of video traffic, traditional video streaming systems are approaching their limits in compression efficiency and communication capacity. To further redu…
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…
INTCP: Information-centric TCP for Satellite Network
Jinyu Yin, Li Jiang, Xinggong Zhang +1
Satellite networks are booming to provide high-speed and low latency Internet access, but the transport layer becomes one of the main obstacles. Legacy end-to-end TCP is designed f…