Gravity Protocol Architecture

Traditional hashing algorithms (MD5, SHA-256) reduce gigabytes of data into a single string. While efficient for equality checks, they fail to describe context.

7-Dimensional Analysis

The Gravity Protocol analyzes data across seven concurrent vectors:

VECTOR 01 Byte Frequency Distribution

VECTOR 02 Local Entropy Variance

VECTOR 03 Structural Pattern Mapping

VECTOR 04 Visual Representation (Hilbert)

API Reference

POST /v1/fingerprint

{
  "hash": "sha256_checksum",
  "gravity_map": {
    "dimensions": [1024, 1024],
    "entropy_score": 0.875,
    "structure_index": 42
  },
  "visual_buffer": "base64_encoded_png..."
}

The NextGen Tech Stack

Protocol Core

VFP (Visual Fingerprint Protocol)

The atomic foundation of the platform. VFP bypasses traditional collision-prone hashing by mapping data to a multidimensional Hilbert-space, creating a structural "identity" that remains sensitive to 1-bit changes.

Diagnostic Layer

7D Lens Technology

A suite of mathematical filters (Energy, Wave, Behavior, Temporal, Diff, Topology, Structure) used to decompose binary streams into forensic artifacts.

Execution Engine

Pyodide (Python in Browser)

We leverage the Pyodide kernel to run full-fledged Scipy and Numpy forensic stacks natively in the browser. This allows for industrial-grade analysis without the files ever leaving the user's secure environment.

Performance Layer

WebAssembly (WASM)

Our CORE-V4 engine is compiled to WASM for

Our CORE-V4 engine is compiled to WASM for near-native performance. This enables real-time 3D rendering of million-point cloud visualizations on standard consumer hardware.

Zero-Knowledge Security

"If you can't see the data, you can't lose it."

By utilizing browser-native execution, VFP NextGen removes the "Server-Side" threat vector entirely. Your forensic laboratory is an air-gapped instance within your browser session.