🔗 Live Demo: https://synthshield.tech

SynthShield

Synthetic Data Defense for Security & Surveillance AI

Overview

SynthShield is an AI-powered platform that generates and analyzes synthetic data to enable secure training and testing of security, surveillance, and healthcare systems without exposing sensitive real-world information.

Built in 24 hours at RevolutionUC Hackathon.

Problem

Modern AI systems in security and healthcare require large amounts of sensitive data. Using real data introduces:

• Privacy risks
• Regulatory challenges
• Data exposure vulnerabilities

Solution

SynthShield replaces sensitive datasets with realistic synthetic data while preserving key statistical patterns. This allows safe development, testing, and validation of AI systems.

Features

• Synthetic data generation for sensitive environments
• Secure AI training without real-world exposure
• Anomaly detection on generated datasets
• Visual comparison between real and synthetic data

Demo

Coming soon (live demo deployed via synthshield.tech)

Tech Stack

• Python (data generation / pipeline)
• AI/ML models (synthetic data + analysis)
• HTML/CSS (frontend demo)
• GitHub Pages / Netlify (deployment)

Use Cases

• Surveillance system training without real footage
• Healthcare data simulation for clinical research
• Cybersecurity testing environments
• Privacy-preserving AI development

Project Structure

synthshield/
├── README.md
├── index.html
├── scanner.py
├── datagen/
│   ├── generate.py
│   ├── annotations/
│   │   └── .gitkeep
│   ├── images/
│   │   └── .gitkeep
│   └── masks/
│       └── .gitkeep