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Recursive Visual Entropy Key Derivation Engine (RVE-KDE)

Project description

Paradox: Recursive Visual Entropy Key Derivation Engine (RVE-KDE)

Paradox Logo

Python Version License: MIT Status: Research Prototype


1. Project Overview & Motivation

Paradox is an experimental cryptographic key derivation engine that maps high-dimensional visual media (images) to symmetric keys deterministically.

Why Visual Entropy?

Traditional key derivation functions (like PBKDF2 or bcrypt) process low-entropy, linear inputs (passwords). In contrast, images represent high-dimensional physical entropy source matrices. Paradox leverages this visual media matrix to establish a deterministic "visual factor" for key agreement, file archiving, and cover-medium key setup.


2. Core Architecture

The pipeline processes input visual data and nonces through seven discrete layers:

  1. Initial Seed Generator: Formulates Seed0 = SHA3-512(ImageHash + Nonce + Timestamp + Version).
  2. Recursive Walker: Slices coordinates modulo dimensions and traverses local adjacent neighbors.
  3. Luminance & Contrast Extractor: Extracts color states, perceived brightness, and local grid standard deviations.
  4. Hash Chain Evolved State: Formulates sequential hash linkages of coordinates, pixel bytes, and neighbor values.
  5. Multi-Layer Recursion Manager: Runs dependent walks in sequence (Layer $n$ seed depends on Layer $n-1$'s final state) to diffuse spatial dependencies.
  6. Entropy Pool Collector: Aggregates SHA3-256 slices from each step into a master entropy pool.
  7. KDF Compressor: Squeezes the pool into 128/256/512-bit keys using HKDF-SHA256 or BLAKE3-KDF.

3. Installation & Developer Setup

Clone the repository and install dependencies in editable mode:

python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

4. Quick Start & Examples

Text Encryption

import paradox

img = paradox.useImage("sample.png")

# Encrypts message and returns metadata envelope
encrypted = paradox.encrypt_text("Confidential message", image=img, security_level="low")

# Decrypts payload deterministically
decrypted = paradox.decrypt_text(encrypted, image=img)
print(decrypted) # "Confidential message"

File Encryption

import paradox

img = paradox.useImage("sample.png")
paradox.encrypt_file("doc.pdf", "doc.pdf.enc", image=img, security_level="low")
paradox.decrypt_file("doc.pdf.enc", "doc_dec.pdf", image=img)

5. API Reference

Category Functions
Image Loading useImage(path), getRandomImage()
Key Derivation generate_key(image, len, level, kdf), generate_key128(), generate_key256(), generate_key512()
Encryption/Decryption encrypt_text(), decrypt_text(), encrypt_file(), decrypt_file()
Diagnostics visualize_walk(), analyze_image()

6. Experimental Validation Results

  • Entropy Density: Derived keys exhibit a Shannon entropy of 7.99946 bits/byte (squeezed via HKDF-SHA256).
  • Chi-Square Goodness-of-Fit: Passed ($p = 0.75 > 0.01$), confirming uniform byte distributions.
  • Avalanche Effect: 50.09% mean bit difference following a 1-bit input offset.
  • Collision Rate: 0.00% collision count over 3,000 keys.

For detailed plots and analysis, see validation_report.md and comparison_report.md.


7. Comparative Benchmark Metrics

Symmetric key (256-bit) latency and memory footprints compared to traditional standards:

Metric Category Paradox (RVE-KDE) PBKDF2-SHA256 HKDF-SHA256 Argon2id (ID) BLAKE3-KDF
Latency LOW 110.35 ms 0.54 ms 0.26 ms 6.37 ms 0.04 ms
Latency HIGH 37,303.10 ms 18.45 ms 0.17 ms 200.25 ms 0.06 ms
Peak Mem HIGH 104.62 MB <0.01 MB <0.01 MB 256.00 MB <0.20 MB
Uniqueness (10k) 100% Unique 100% Unique 100% Unique 100% Unique 100% Unique
Vulnerabilities Nonce-reuse risk GPU cracking Salt reuse Param tuning Context collision

8. Citation & Acknowledgements

If you use Paradox in your cryptographic research or academic publications, please cite it using:

@software{paradox_kdf2026,
  author = {Chirag Ferwani},
  title = {Paradox: Recursive Visual Entropy Key Derivation Engine},
  url = {https://github.com/chiragferwani/paradox},
  version = {1.0.0},
  year = {2026}
}

Acknowledgements

  • Matplotlib and NumPy contributors for diagnostic utilities.
  • The Google DeepMind pair-programming agent workspace.
  • Established standard KDF authors (Argon2, PBKDF2, BLAKE3).

9. License

Licensed under the MIT License - see LICENSE for details.


[!WARNING] Paradox is an experimental research-oriented key derivation framework and should not be considered a replacement for established cryptographic standards such as Argon2, PBKDF2, HKDF, or BLAKE3.

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