https://github.com/nadhirfr/rf-ids
Machine Learning Based - Intrusion Detection System
https://github.com/nadhirfr/rf-ids
cic-ids-2018 data-science ddos ddos-detection ddos-mitigation django-framework intrusion-detection intrusion-detection-system machine-learning machinelearning random-forest sflow sflow-rt software-defined-network
Last synced: about 2 months ago
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Machine Learning Based - Intrusion Detection System
- Host: GitHub
- URL: https://github.com/nadhirfr/rf-ids
- Owner: nadhirfr
- Created: 2019-07-05T22:04:00.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-06-21T22:16:18.000Z (over 3 years ago)
- Last Synced: 2025-01-31T23:05:00.322Z (11 months ago)
- Topics: cic-ids-2018, data-science, ddos, ddos-detection, ddos-mitigation, django-framework, intrusion-detection, intrusion-detection-system, machine-learning, machinelearning, random-forest, sflow, sflow-rt, software-defined-network
- Language: CSS
- Homepage:
- Size: 4.32 MB
- Stars: 31
- Watchers: 1
- Forks: 2
- Open Issues: 5
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Random Forest - IDS
This is an Intrution Detection System with Machine Learning Based (Random Forest). This IDS used to detect DDoS Attack in Software-Defined Network with utilizing sFlow-RT (sFlow protocol). The analyze of Machine Learning Model can be found here: https://github.com/nadhirfr/cic-ids-2018
[](https://ko-fi.com/H2H146AUD)
Feature:
- Django Framework
- API (WebSocket and HTTP)
- Realtime Attack Alert
- Read Traffic from sFlow-RT
- Full async process (Django-Channels)
Dashboard 
Log 
__HTTP API Documentation:__
| URL : | http://ip_address/api/?sec=latestLog&limit=limitShow |
|------------|------------------------------------------------------|
| Method : | GET |
| Example : | http://127.0.0.1/api/?sec=10&limit=5 |
| | Get 5 data in last 10 seconds |
*GET status of service : http://ip_address/api/status/*
__WS Access URL : ws://ip_address/ws/api/__