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The MultiFactorAuthApp is an advanced Android security solution that implements a Triple-Layer Authentication framework. It moves beyond static credentials by integrating behavioral biometrics specifically Keystroke Dynamics and Pattern Rhythm Analysis to verify the identity of the user based on "how" they interact with the device.

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XoxoKiwi/MultiFactorAuthApp

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MultiFactorAuthApp

A sophisticated Android security application implementing a Triple-Layer Authentication system. This project utilizes behavioral biometrics—specifically Keystroke Dynamics and Pattern Rhythm Analysis—to ensure the user is the genuine owner.

⚙️ Security Layers

  1. Biometric Layer: Initial hardware-level fingerprint verification using the Android Biometric API.
  2. Pattern Dynamics: A custom-built pattern lock that analyzes the speed and consistency of the drawing motion.
  3. Keystroke Dynamics: A password field that utilizes a custom QIFNN (Quantum-Inspired Firefly Neural Network) logic to verify typing rhythm.

🧠 The "Brain": QIFNN Logic

The core of the app's security lies in the QIFNN.kt engine. Inspired by the Firefly Algorithm's optimization capabilities, it features:

  • Asymmetric Bias: Penalizes slow, hesitant input (intruder behavior) by 3.5x while remaining lenient toward fast, muscle-memory input (owner behavior).
  • Adaptive Learning: Updates the user's profile after every successful login using an Alpha Learning Rate, mimicking the "attractiveness" and "movement" mechanics of the Firefly algorithm to stay aligned with the user.
  • Jitter Detection: Uses Standard Deviation to identify inconsistent "shaky" input typical of non-genuine users.

🛡️ Privacy & Security

  • Zero-Knowledge Storage: All patterns and passwords are saved as SHA-256 hashes.
  • Anti-Extraction: allowBackup is disabled to prevent data theft via ADB or cloud backups.
  • Lifecycle Protection: Activities auto-terminate on onStop() to prevent background bypass.

About

The MultiFactorAuthApp is an advanced Android security solution that implements a Triple-Layer Authentication framework. It moves beyond static credentials by integrating behavioral biometrics specifically Keystroke Dynamics and Pattern Rhythm Analysis to verify the identity of the user based on "how" they interact with the device.

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