WithHades/network_traffic_classification_paper
收集了部分将机器学习应用于网络流量分类的论文
This collection helps network security analysts, operations engineers, and researchers stay updated on advancements in classifying network traffic. It provides a curated list of research papers, some with translations, that detail how machine learning and deep learning techniques are applied to identify and categorize different types of network activities, including encrypted and IoT traffic. The collection helps practitioners understand various methodologies for traffic classification and intrusion detection.
174 stars. No commits in the last 6 months.
Use this if you are a network professional or researcher looking for a consolidated resource of academic papers on machine learning applications in network traffic classification.
Not ideal if you need a software tool or code implementation for network traffic classification, as this is a collection of papers, not an active project.
Stars
174
Forks
26
Language
—
License
—
Category
Last pushed
Jul 05, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/WithHades/network_traffic_classification_paper"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GACWR/OpenUBA
A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for...
nfstream/nfstream
NFStream: a Flexible Network Data Analysis Framework.
echowei/DeepTraffic
Deep Learning models for network traffic classification
faucetsdn/poseidon
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire...
CESNET/cesnet-datazoo
CESNET DataZoo: A toolset for large network traffic datasets