mvoassis/CIC-DDoS2019-DeepLearning
:shield: A GRU deep learning system against attacks in Software Defined Networks (SDN).
This system helps network security professionals automatically identify and flag Distributed Denial of Service (DDoS) attacks within Software Defined Networks (SDN). It takes network traffic data as input and provides an alert or classification indicating the presence of a DDoS attack. Network administrators and security operations center (SOC) analysts would use this to protect their networks.
No commits in the last 6 months.
Use this if you manage Software Defined Networks and need an automated solution to detect DDoS attacks efficiently.
Not ideal if you are looking for a system to prevent attacks or to analyze non-DDoS related network anomalies.
Stars
34
Forks
10
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 19, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mvoassis/CIC-DDoS2019-DeepLearning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
santhisenan/DeepDefense
DDoS attack detection using BLSTM based RNN
GAR-Project/project
DDoS attacks detection by using SVM on SDN networks.
MeherRushi/FlowSentryX
FlowSentryX is an open-source XDP-based fast packet processing DOS and DDOS Mitigation Framework...
ReubenJoe/DDoS-Detection
Detailed Comparative analysis of DDoS detection using Machine Learning Models
ash0545/sdn-ml-ids
SDN Topology Emulation and Development of Dataset for ML-Based Intrusion Detection through the...