
Personal Secret Vault with Biometric Lock Simulation
Why Choose This Project?
With rising concerns about personal data privacy, users seek ways to securely store sensitive information (notes, files, passwords, images, etc.) using biometric authentication. This project simulates biometric locking mechanisms (like fingerprint or face recognition) for a personal vault that encrypts user data using strong cryptography. Ideal for cybersecurity, full-stack, or AI-integrated projects.
What You Get in This Project
A secure personal vault web app where users can store sensitive data (text, files, images) behind a biometric simulation lock, with AES encryption, authentication, and access logs.
Technology Stack
Layer | Tech/Tools |
---|---|
Frontend | HTML, CSS, Bootstrap, JavaScript, WebRTC (for webcam access) |
Backend | Node.js (Express) / Java Spring Boot / Django |
Biometric Sim | Simulated fingerprint/face ID via webcam using TensorFlow.js |
Encryption | AES-256 for vault content |
Database | MongoDB / MySQL / PostgreSQL |
Storage | Encrypted local storage or cloud (S3/Firebase) |
Auth | JWT / Spring Security / Django Auth |
Key Features
Feature | Description |
---|---|
Biometric Lock Simulation | Face/fingerprint scan simulation using webcam + ML model |
User Login & Registration | Traditional login with 2FA or password + biometric sim |
Secret Vault Area | Users can store text notes, files, or links securely |
AES-256 Encryption | All data in vault is encrypted before saving |
Encrypted Image/File Support | Upload and store private files securely |
Face Recognition (Simulated) | Recognizes user's face (via webcam) using client-side TensorFlow.js model |
Access Logs | Record each login, biometric match, or access attempt |
Auto Lock Timeout | Vault auto locks after inactivity |
Anti-Brute-Force | Lock account after N failed unlock attempts |
Export/Import Vault | User can export or import vault content (encrypted backup) |
Biometric Simulation Options
Option | Technology | Description |
---|---|---|
Face ID Sim | TensorFlow.js + Webcam | Detect face via browser, match with pre-trained embedding |
Fingerprint UI | HTML/CSS Animation + Password | Fake scanner interface + pattern/pin simulation |
Mobile Biometric | Use WebAuthn on mobile devices | Real biometric prompt on supported phones (optional) |
Access Control & Flow
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User logs in with email/password
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System requests biometric simulation:
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Webcam opens → face detection starts
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Model compares face to stored embedding
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If biometric success → decrypt vault
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If failed → deny access, log attempt