DDoS-Detection and Machine-Learning-Based-Detection-of-Distributed-Denial-of-Service-DDoS-Attacks
Maintenance
0/25
Adoption
7/25
Maturity
8/25
Community
17/25
Maintenance
6/25
Adoption
3/25
Maturity
13/25
Community
0/25
Stars: 31
Forks: 9
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
Stars: 4
Forks: —
Downloads: —
Commits (30d): 0
Language: —
License: MIT
No License
Stale 6m
No Package
No Dependents
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 Machine-Learning-Based-Detection-of-Distributed-Denial-of-Service-DDoS-Attacks
acetinkaya/Machine-Learning-Based-Detection-of-Distributed-Denial-of-Service-DDoS-Attacks
Machine Learning-Based Detection of Distributed Denial-of-Service (DDoS) Attacks
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work