niherhalder/Security_Monitoring_Dashboard

# Security Monitoring Dashboard Python-based cybersecurity monitoring and log analysis project designed to simulate a lightweight Security Operations Center (SOC) workflow for detecting suspicious activities, analyzing security logs, generating dashboard visualizations, and creating automated security reports. # Project Overview The **Security Monitoring Dashboard** is a cybersecurity automation project developed using Python. This project simulates a basic SOC (Security Operations Center) environment where system logs are analyzed to identify suspicious activities, classify event severity levels, estimate security risks, and generate automated monitoring reports. The dashboard also creates graphical visualizations for better understanding of security events and threat patterns. This project is suitable for: - Cybersecurity portfolio projects - SOC analyst practice - Threat detection learning - Log analysis automation - Security monitoring simulation - Detection engineering foundations - Python cybersecurity development # Features - Automated security log analysis - Severity-based event classification - Suspicious activity detection - Risk level estimation - Dashboard chart generation - Pie chart visualization - Automated security report generation - SOC-style monitoring workflow - Lightweight and beginner-friendly implementation - Screenshot documentation support # Severity Levels Detected The system detects and analyzes the following security log severity levels: - INFO - WARNING - ERROR - FAILED # Technologies Used - Python - File Handling - String Processing - Log Parsing - Matplotlib - Cybersecurity Automation - Security Monitoring Concepts # Project Structure Security_Monitoring_Dashboard/ │ ├── screenshots/ │ ├── project_folder.png │ ├── dashboard_chart_view.png │ ├── pie_chart_view.png │ ├── report_preview.png │ └── terminal_execution.png │ ├── dashboard.py ├── .gitignore ├── security_logs.txt ├── dashboard_report.txt ├── dashboard_chart.png ├── pie_chart.png ├── requirements.txt └── README.md # Installation Install required libraries using: pip install -r requirements.txt # Run the Project Execute the project using: python dashboard.py # Output The project automatically generates: dashboard_report.txt dashboard_chart.png pie_chart.png # Example Generated Report ===================================== Security Monitoring Dashboard Report ===================================== Generated: 2026-05-29 07:43:57 Total Logs Analyzed: 12 Total Issues Detected: 9 Severity Count: INFO: 3 WARNING: 3 ERROR: 4 FAILED: 2 Risk Summary: Risk Level: HIGH # Example Detection Scenarios The dashboard can identify security-related events such as: - Multiple failed login attempts - Unauthorized SSH access attempts - Malware detection alerts - High CPU usage warnings - Database connection failures - Remote login blocking events - Suspicious PowerShell activity - Abnormal system behavior indicators # Risk Level Classification The project estimates overall system risk based on detected security events. Possible classifications include: - LOW - MEDIUM - HIGH - CRITICAL # Dashboard Visualizations The project generates visual analytics for security monitoring. ## Dashboard Bar Chart Displays the count of severity-based log events. ## Pie Chart Visualization Displays percentage distribution of detected security events. # Screenshots Project screenshots are available inside the `screenshots` folder. Included screenshots: - project_folder structure - Dashboard chart visualization - Pie chart visualization - Report preview - Terminal execution # Cybersecurity Concepts Demonstrated This project demonstrates practical cybersecurity concepts including: - Security Operations Center (SOC) workflow - Security log monitoring - Threat detection basics - Event severity analysis - Incident reporting - Security automation - Detection engineering fundamentals # Future Improvements Planned future enhancements: - Real-time log monitoring - Live dashboard interface - AI-powered threat explanation - Email alert integration - Threat scoring engine - SIEM integration simulation - CSV/XLSX export support - Flask/Django web dashboard - Machine learning anomaly detection # Version Current Version: `v1.0` ## v1.0 Features - Security log analysis - Severity counting - Risk estimation - Dashboard visualization - Automated report generation - Screenshot documentation # Author Niher Halder Cybersecurity Engineer | Threat Detection & Security Automation