NeoCrypt-HSI is a cutting-edge cryptographic framework designed specifically for the secure transmission and storage of 16-bit Hyperspectral Image (HSI) cubes. By integrating high-dimensional chaotic maps, DNA-inspired algebraic rules, and Quantum Key Distribution (QKD) seeding, this project provides "unconditional security" without compromising computational speed or data integrity.
- Native 16-Bit Support: Unlike standard 8-bit image encryption, this pipeline operates directly on 16-bit HSI data, preserving the high-fidelity spectral signatures essential for remote sensing and scientific analysis.
- Lossless Data Integrity: Guarantees 100% bit-perfect restoration (MSE = 0, PSNR = ∞) between original and decrypted datasets.
- Low-Spec Hardware Optimization: Uses Statistical Quantization (Rank Mapping) instead of heavy index-based sorting, allowing the algorithm to encrypt massive
.matfiles on consumer-grade hardware (e.g., Intel i3, 8GB RAM) without memory crashes. - Plaintext-Dependent Security: Leverages U-PEP (Universal Plaintext-Equivalent Perturbation) extraction to ensure that the encryption keys are intrinsically linked to the image content, providing total immunity against known-plaintext attacks.
The encryption process follows a sophisticated three-stage volumetric pipeline:
- QKD Integration: The initial master key is seeded via simulated Quantum Key Distribution.
- U-PEP Extraction: A SHA-512 hash of the image content is merged with the QKD key to generate highly sensitive chaotic parameters.
- Chaotic Engine: A high-speed Numba-accelerated generator creates four distinct chaotic sequences (X, Y, Z, K).
- Spatial Confusion: Pixels are relocated using chaotic circular row and column shifts, breaking the visual structure of the HSI cube.
- Spectral Scrambling: The "spectral signature" of each pixel is rotated across the Z-axis (bands), obfuscating the relationships between contiguous spectral frequencies.
- 16-Bit Splitting: Pixel data is split into high and low bytes and encoded into DNA bases (A, T, C, G).
- Dynamic Rule Selection: Eight distinct DNA algebraic XOR rules are applied pixel-by-pixel, driven by the chaotic Z-sequence, ensuring high sensitivity and massive entropy.
The methodology has been benchmarked against industry-standard metrics:
| Metric | Achieved Result | Ideal Target |
|---|---|---|
| Information Entropy | ~15.999x | 16.0 (for 16-bit data) |
| NPCR | > 99.6% | > 99.6% |
| UACI | ~ 33.4% | ~ 33.4% |
| Correlation Coeff. | ~ 0.000x | 0.0 (No correlation) |
| Restoration MSE | 0.0 | 0.0 |
- Python 3.8+
- Core Libraries:
numpy,scipy,hashlib,time,gc - Acceleration:
numba(for JIT-compiled chaos cores) - Hardware Monitor:
psutil(for dynamic RAM management)
- Load Dataset: Import your HSI
.matfile (e.g., Pavia University, Indian Pines). - Run U-PEP & Chaos Cell: Extract keys and generate chaotic sequences. The system will automatically detect if your RAM is sufficient and apply Statistical Quantization if needed.
- Execute Encryption: Run the vectorized encryption cell to transform the image into ciphertext.
- Analyze Results: Use the Comprehensive Security Audit cell to verify entropy and avalanche effects.
- Exploration of QKD Integration Strategies: Investigate and evaluate various physical and logical frameworks for integrating Quantum Key Distribution into the existing 16-bit pipeline to establish an unconditionally secure key exchange layer.
This project is developed for research and academic purposes.