Recursive Visual Entropy Key Derivation Engine (RVE-KDE)
Project description
Paradox: Recursive Visual Entropy Key Derivation Engine (RVE-KDE)
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:
- Initial Seed Generator: Formulates
Seed0 = SHA3-512(ImageHash + Nonce + Timestamp + Version). - Recursive Walker: Slices coordinates modulo dimensions and traverses local adjacent neighbors.
- Luminance & Contrast Extractor: Extracts color states, perceived brightness, and local grid standard deviations.
- Hash Chain Evolved State: Formulates sequential hash linkages of coordinates, pixel bytes, and neighbor values.
- Multi-Layer Recursion Manager: Runs dependent walks in sequence (Layer $n$ seed depends on Layer $n-1$'s final state) to diffuse spatial dependencies.
- Entropy Pool Collector: Aggregates SHA3-256 slices from each step into a master entropy pool.
- 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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