Cybersecurity Dashboard

This is a Streamlit-based web application designed to visualize and analyze cybersecurity metrics, providing real-time insights into potential threats, security vulnerabilities, and overall system performance.

The Cybersecurity Dashboard provides a user-friendly interface for both technical and non-technical users to monitor critical aspects of a system's security health.

Features

• Real-Time Threat Monitoring: Track and visualize cybersecurity threats, including malware, phishing attacks, and other vulnerabilities.
• Security Metrics: Analyze key metrics such as failed login attempts, unauthorized access, network activity, and more.
• Data Visualization: Interactive charts and graphs to help users better understand their system’s security status.
• Alerts and Notifications: Displays warnings for critical threats and vulnerabilities that need immediate attention.
• Customizable Views: Select specific time periods or metrics to analyze, giving users a detailed and personalized security overview.

Technology Stack

• Frontend: Streamlit – A Python library that allows easy creation of data applications with minimal code.
• Backend: Python for data processing and analysis.
• Data Visualization: matplotlib and plotly for generating interactive charts.
• Deployment: The app is hosted on Streamlit Cloud.

Installation

To run this application locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/ajitagupta/cybersecurity-dashboard.git

2. Navigate into the project directory:

   cd cybersecurity-dashboard

3. Install the required dependencies:

   pip install -r requirements.txt

4. Run the Streamlit app:

   streamlit run cybersecurity_dashboard.py

How to Use

1. Launch the application locally or access the live app here.
2. Navigate through the dashboard to view real-time security metrics.
3. Customize the data view by selecting different time frames or security metrics.
4. The dashboard automatically updates as new data comes in, ensuring you always have the latest information.

Contributing

Contributions are welcome! If you want to improve this dashboard or fix any issues, feel free to submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgements

• Thanks to the Streamlit community for building an amazing tool for building data-driven web apps.
• Special thanks to all contributors and users who have helped improve this project.