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User Behaviour Analytics

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Python NPM HTML CSS JS

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To aggregate and analyze machine data for Operational Intelligence using User Behavior Analytics(UBA). It creates multi-dimensional behavior baselines around users, service accounts, devices, and applications then executing unsupervised machine learning algorithms to generate anomalies and threats. Thus providing Insider security for an organization.

Use Case:

  • Advanced Threat Detection
  • Higher Productivity
  • Threat Hunting
  • Enhance Visibility and Detection
  • Fraudulent website Activity

Installation

Fork this repository (Click the Fork button in the top right of this page, click your Profile Image) Clone your fork down to your local machine

git clone https://github.com/your-username/UBA.git
  1. Install pip3 if you don't have it already
    curl "https://bootstrap.pypa.io/get-pip.py" -o "get-pip.py"
    python3 get-pip.py     
    sudo python3 get-pip.py
  1. Install the python dependencies
pip3 install requirements.txt
  1. Install HADOOP and JDK
  2. Configure Spark environment by running spark_env.sh
bash spark_env.sh 
OR
./spark_env.sh
  1. Run the make file
make
  1. Point your browser to localhost:3000 to view the UI and localhost:5000 for viewing the Flask app running

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UEBA Solution for Insider Security

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  • Python 55.0%
  • HTML 34.8%
  • Shell 8.6%
  • JavaScript 1.3%
  • Makefile 0.3%