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completed security-research

Steganography Research (Published)

My published peer-reviewed research natively hiding data within images using advanced cryptographic encodings to mathematically defeat detection tools.

Started: January 1, 2025
Completed: January 31, 2025
GitHub Repository
1,310
Trials Evaluated
1
Publications

Tags

steganographyresearchpublicationimage-processing

Technologies

Python OpenCV NumPy PyCryptodome AES-128

Architecture

Steganography Pipeline

AES-256 encrypted LSB steganography with CTR DRBG

Secret Message
Plaintext to be hidden
CTR DRBG
Cryptographic random number generator
AES-256 Encrypt
Symmetric encryption of message
LSB Embedding
Least Significant Bit steganography
Stego Image
Output image containing hidden data

AES-256 Encryption

Military-grade symmetric encryption with 256-bit key length. Provides confidentiality even if steganography is detected.

CTR DRBG

NIST SP 800-90A compliant deterministic random bit generator. Ensures cryptographic quality randomness for key generation.

LSB Steganography

Least Significant Bit embedding in pixel values. Imperceptible to human vision while maintaining high capacity.

AES-256Military-Grade Encryption

Overview

Published research in Springer LNNS (vol 285) on improving steganography imperceptibility using PVD, LSB substitution, and modulo encoding with NIST SP 800-90A CTR_DRBG. 1,310 embedding trials evaluated with PSNR, MSE, and SSIM metrics.

Project Details

This project is part of the research portfolio focusing on security-research.

Technologies Used

  • Python
  • OpenCV
  • NumPy
  • PyCryptodome
  • AES-128

Repository

Full source code available on GitHub: https://github.com/alazkiyai09/pvd-lsb-modulo-steganography

Key Features

  • Production-ready implementation
  • Comprehensive documentation
  • Unit tests and integration tests
  • Docker support for containerization

Results

  • Successfully deployed and tested
  • Meets all project requirements
  • Documented with comprehensive README