AntiVE-BehaviorWatch

Embedded AI-powered human behavior verification for cybersecurity research.

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What is AntiVE-BehaviorWatch?

AntiVE-BehaviorWatch is a Windows-based cybersecurity research project that explores a new approach to execution control using embedded artificial intelligence.

Instead of relying on traditional anti-analysis techniques such as virtual machine detection, sandbox detection, debugger checks, or hardware fingerprinting, the project uses an embedded GRU (Gated Recurrent Unit) neural network to determine whether a real human is interacting with the system.

The model analyzes real-time mouse behavior—including cursor movement, velocity, acceleration, jerk, angular velocity, idle patterns, and motion characteristics—to make an intelligent runtime decision before allowing the protected execution path to continue.

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Architecture

Mouse Movement
       │
       ▼
Feature Extraction
       │
       ▼
Embedded GRU Neural Network
       │
       ▼
Behavior Classification
       │
 ┌─────┴────────┐
 │              │
 ▼              ▼
Human      Idle / Artificial
Verified      Behavior
 │              │
 ▼              ▼
Continue     Abort
Execution

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Behavioral Features

The embedded model analyzes multiple behavioral features:

• Cursor Distance
• Cursor Velocity
• Acceleration
• Jerk
• Mouse Angle
• X-axis Movement
• Y-axis Movement
• Idle State
• Idle Streak Length

These features are collected continuously over multiple observation phases before inference.

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Features

• Embedded GRU neural network
• Offline AI inference
• No external AI runtime required
• Real-time behavioral telemetry
• Human interaction verification
• Multi-phase analysis
• Majority voting decision engine
• Lightweight C implementation
• Windows-native application
• Embedded model weights
• Runtime behavior classification

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Disclaimer

This project is intended strictly for cybersecurity research, machine learning experimentation, education, and authorized security testing.

It demonstrates how embedded AI can be used for behavioral verification and runtime decision-making. It is not intended for unauthorized or malicious use.

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Author

Nirvana (0xNirSec)

"Trust behavior, not the environment."