收集了部分将机器学习应用于网络流量分类的论文

heiFIP: A tool to convert network traffic into images for ML use cases

CSNet 23 - A generalizable approach for network flow image representation for deep learning

Code and example data for transcriptional-data-guided brain network classification

Opportunities and challenges in partitioning the graph measure space of real-world networks

CyberBERT is a deep learning model for network traffic classification, leveraging the DistilBERT architecture. It processes network flow data to classify various types of network traffic, including benign and malicious patterns, with high accuracy.