DDoS-Detection and DDoS-Detection-ML

DDoS-Detection
32
Emerging
DDoS-Detection-ML
24
Experimental
Maintenance 0/25
Adoption 7/25
Maturity 8/25
Community 17/25
Maintenance 0/25
Adoption 1/25
Maturity 11/25
Community 12/25
Stars: 31
Forks: 9
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 1
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No License Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About DDoS-Detection

ReubenJoe/DDoS-Detection

Detailed Comparative analysis of DDoS detection using Machine Learning Models

This project helps network security teams and operations engineers identify Distributed Denial of Service (DDoS) attacks. It takes network traffic data as input and uses various machine learning models to classify whether the traffic is normal or part of a DDoS attack. The output helps security professionals quickly detect and respond to these critical threats.

network-security DDoS-detection cybersecurity threat-detection network-operations

About DDoS-Detection-ML

FaizanZaheerGit/DDoS-Detection-ML

Various supervised machine learning techniques on the highly optimized NSL-KDD dataset to create an efficient and accurate predictor of possible intrusions on a network.

Scores updated daily from GitHub, PyPI, and npm data. How scores work