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Project based on SVM and Random Forest to detect Intrusion on network traffic

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DhruvBhirud/Intrusion-Detection-System-using-ML

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Intrusion-Detection-using-ML

Project Idea: Making an Intrusion Detection using Machine Learning

Contributors:

    1. Dhruv Bhirud
    2. Vaishnavi Powar
    3. Ariful Hauqe Mollah

Problem Statement:

Intrusion-Detection-using-ML: The aim of the project is to train model for Intrusion Detection task.

    Step 1: Understanding and Cleaning up the data. Generating data insights.
    Step 2: Training multiple classifiers models on the dataset.
    Step 3: Generating report for comparing model results.
    Step 4: Developing Flask server for users to select and input test data.

Model Training and Testing Done on Google Colab

Notebook used to train Random Forest and SVM model: Here(GitHub) or Here(Colab)

Live Demo

Intrusion Detection using ML

Setup

To install requirements, run the following command.

$ pip install -r requirements.txt

Steps for starting server.

$ export FLASK_APP=app.py
$ python -m flask run