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SABMIS: sparse approximation based blind multi-image steganography scheme.

Rohit Agrawal1,2, Kapil Ahuja1, Marc C Steinbach3

  • 1Computer Science and Engineering, Indian Institute of Technology Indore, Indore, India.

Peerj. Computer Science
|December 19, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces SABMIS, a novel steganography scheme for hiding multiple secret images within a cover image. SABMIS achieves high embedding capacity and excellent visual quality for both cover and secret images, enhancing security against attacks.

Keywords:
ADMMImage processingLASSOOptimizationSparse approximationSteganography

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Area of Science:

  • Computer Science
  • Information Security
  • Image Processing

Background:

  • Steganography, the art of hiding information, faces challenges in embedding multiple secret images within a cover image while maintaining quality and security.
  • Existing methods often struggle to balance embedding capacity, visual fidelity, and resistance to steganographic attacks.

Purpose of the Study:

  • To develop a steganography scheme, termed SABMIS (Sparse Approximation Blind Multi-Image Steganography), with enhanced embedding capacity for multiple grayscale secret images.
  • To ensure high visual quality of both the stego-image and the extracted secret images.
  • To improve the resistance of the stego-image against steganographic attacks.

Main Methods:

  • A novel embedding rule is proposed, hiding secret image sparse coefficients into oversampled cover image sparse coefficients in a staggered manner.
  • The stego-image is constructed using the Alternating Direction Method of Multipliers (ADMM) to solve a Least Absolute Shrinkage and Selection Operator (LASSO) formulation.
  • Secret images are extracted using the reverse of the embedding rule.

Main Results:

  • SABMIS achieves embedding capacities of 2, 4, 6, and 8 bits per pixel (bpp) for embedding one, two, three, and four secret images, respectively.
  • For two and three secret images, embedding capacities are significantly higher (3x and 6x) than existing methods.
  • The scheme demonstrates minimal deterioration in stego-image quality (visually and >30 dB PSNR) and near-perfect extraction of secret images, with enhanced security.
  • SABMIS executes in minutes and is applicable to real-world scenarios like secure medical image transmission.

Conclusions:

  • SABMIS offers a superior solution for multi-image steganography, outperforming existing methods in embedding capacity and quality preservation.
  • The scheme provides robust security against steganographic attacks, validated through extensive experiments and numerical measures.
  • SABMIS is a practical and efficient solution for secure image data transmission.