ML Application · Python
pcap-ml-traffic-classifier
A curated project showcasing A Machine Learning-Powered PCAP Classification Model
What it is
This repository provides a machine learning-based network intrusion detection system that extracts L3/L4 features from PCAP files using Scapy and trains a CatBoost classifier to distinguish benign from malicious traffic. It includes a threat intelligence reporting feature that aggregates malicious packets by source IP address.
- catboost
- catboost-classifier
- catboost-model
- catboost-tutorial
- cybersecurity
- machine-learning
- machine-learning-models
- machinelearning-python
- ml
- ml-engineering
Where it counts
- Machine Learning90%
- Data Science30%
- MLOps10%
How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.
Around it on the Machine Learning board
Whole board- 22, shared rankfresta-edgeML Application · Python57.4ImplementationTiago SantosMachine Learning
- 22, shared rankmines-livive-netTraining Experiment · JavaScript57.4ImplementationJarad PeckenpaughMachine Learning
- 25pcap-ml-traffic-classifierML Application · Python56.2ImplementationPop AlexandruMachine Learning
- 26bf16-update-realization-in-transformersTraining Experiment · Python55.8ImplementationRickMachine Learning
- 27bf16-4-3-overshoot-ratio-investigationTraining Experiment · Python55.5ImplementationRickMachine Learning
