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This project is a network intrusion detector that employs machine learning methods to discriminate between good (normal) and bad (intrusions/attacks) connections. The Flask framework is used to build the UI, while the KDD Cup 1999 dataset is utilised for training. The major technologies utilised in this project are Python, Flask, and Scikit-learn.

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Kartheekbandi/Intrusion-Detection

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Network Intrusion Detection

This project is a network intrusion detector, a predictive model built to distinguish between bad connections (intrusions/attacks) and good (normal) connections. The dataset used is KDD Cup 1999 dataset and various machine learning algorithms have been used to train the model. The UI has been developed using flask framework.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Python 3
  • Required Libraries : pandas, numpy, sklearn, flask, pickle

Installing

  • Clone the repository
    git clone https://github.com/<username>/network-intrusion-detection.git
  • Install the required libraries
    pip install -r requirements.txt
  • Run the app
    python app.py

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About

This project is a network intrusion detector that employs machine learning methods to discriminate between good (normal) and bad (intrusions/attacks) connections. The Flask framework is used to build the UI, while the KDD Cup 1999 dataset is utilised for training. The major technologies utilised in this project are Python, Flask, and Scikit-learn.

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