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ai-behavior-forensics

A browser-based forensic typing analysis framework to distinguish genuine human cognition from AI-assisted transcription.

ThoughtTrace Pro

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ThoughtTrace Pro* is a browser-based forensic typing analysis framework designed to distinguish genuine human cognition from AI-assisted transcription.

Unlike traditional NLP-based AI detectors (which analyze the final text), ThoughtTrace analyzes the behavioral biometrics of the writing process.

The Problem

Current AI detection tools fail when users manually transcribe AI-generated text or perform heavy "AI-assisted editing." They also struggle with false positives, accusing genuine students of cheating.

The Solution: Behavioral Biometrics

ThoughtTrace monitors keystroke dynamics, context switching, and input entropy to create a Session Audit Trail. It doesn't judge the words; it judges how the words were typed.

Core Engines

  • Baseline Calibration: Establishes a personalized typing fingerprint (Jitter/CV) before the session begins to prevent device bias.
  • Sync Coverage Algorithm: Compares DOM text length with actual keystroke events. Instantly flags massive clipboard injections (Copy-Paste).
  • Cognitive Entropy (CV) Analysis: Analyzes the Coefficient of Variation (CV) of keystroke delays. Authentic human thought produces non-linear, rhythmic jitter. Manual transcription of AI text produces mechanical, linear input.
  • Focus Loss Tracking: Monitors tab-switching and window blur events to detect "Synthesizer" behavior (reading from an external AI window).

Quick Start

This is a zero-dependency, local-first vanilla JavaScript prototype.

  1. Clone the repository.
  2. Open index.html in any modern browser.
  3. Complete the Initial Calibration to unlock the secure buffer.

Privacy First

100% Local Processing. ThoughtTrace Pro relies on localStorage and client-side processing. No keystroke data or written content is ever sent to a remote server.

Final Output

Generates a downloadable PDF Forensic Audit Report containing a timeline of behavioral shifts (e.g., [CRITICAL_PASTE] followed by [HUMAN_RECOVERY]), providing educators with context rather than just a binary score.

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A browser-based forensic typing analysis framework to distinguish genuine human cognition from AI-assisted transcription.

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