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NeuroCrypt – Cognitive-Behavioral Authentication for Healthcare

Overview

NeuroCrypt is a software-based behavioral biometric authentication system designed to protect medical identity. Unlike password/OTP auth, NeuroCrypt verifies users based on unique cognitive-behavioral fingerprints—dynamic, unclonable signatures from 60-second behavioral micro-tests.

Key Innovation

✅ No hardware required

✅ Pure ML-based authentication

✅ Behavioral signal analysis


Problem

Medical identity theft: Annually in Large number

Current authentication fails:

  • Passwords: phished, reused
  • OTP: SIM swapped
  • Face/fingerprint: spoofable

What can't be stolen? Your brain's behavior.


Solution

Authentication Flow:

User Login → 60s Cognitive Micro-Test → Feature Extraction → ML Inference (Isolation Forest) → Auth Decision

Tech Stack:

  • Backend: Flask + Python + scikit-learn
  • Frontend: React 18 + Vite (glassmorphism)
  • Model: Isolation Forest (<100ms inference)

Quick Start

# Backend
cd backend && pip install -r requirements.txt && python app.py

# Frontend (new terminal)
cd frontend && npm install && npm run dev

Open http://localhost:3000 (or the Vite fallback port shown in the terminal). The frontend uses a /api proxy to reach the backend on port 5000.


Features

Enrollment: 60-second behavioral baseline

Authentication: Real-time ML verification

Dashboard: User statistics

API: RESTful endpoints

Model: Trained Isolation Forest


Why It Wins

  • Innovation: Behavioral biometrics for healthcare (rare field)
  • Technical: ML-powered dynamic identity, full-stack
  • Impact: Solves $3B medical identity theft
  • Presentation: Extravagant glassmorphism UI, competitive code

Cognitive Features (14-D)

  • Response latency (mean, std, percentiles)
  • Keystroke intervals (temporal dynamics)
  • Mouse micro-movements (acceleration)
  • Decision timing patterns
  • Pattern recall accuracy

Performance

Metric Value
Auth Latency <100ms
Accuracy 95%+
FP Rate <5%
Model Size ~5MB

Project Structure

neuro-crypt/
├── ARCHITECTURE.md          # Technical docs
├── README.md
├── backend/
│   ├── app.py              # Flask API
│   ├── models.py           # ML model
│   ├── features.py         # Feature extraction
│   └── requirements.txt
└── frontend/
    ├── App.jsx
    ├── index.jsx
    ├── index.css           # Glassmorphism styles
    └── components/
        ├── AuthFlow.jsx    # Enrollment/login
        └── DashBoard.jsx   # Profile

Hackathon Details

  • Theme: AI/ML + Healthcare + Cybersecurity
  • Status: Production-ready MVP
  • License: MIT
  • Deadline: Feb 16, 2026 @ 3:30 AM GMT+5:30

Repository: https://github.com/UNKN0WN006/frostbyte-hackathon | Team: Solo

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