Authors:
Lekshmi Kalinathan, K. Devi, S. Benila, Vasudev Arun Ganesh, R. Santhosh Krishna, Anudeep Lam

Addresses:
School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.

Abstract:

Pixel Value Differencing (PVD) is one of the most widely used steganographic techniques, which relies on the differences in pixel intensities between adjacent pixels to conceal secret data. By altering these differences, PVD enables efficient data hiding, minimising significant image-quality degradation from slight, often unnoticeable alterations in pixel values to the human eye. However, classical PVD struggles to achieve an optimal balance between capacity and visual invisibility. This work introduces an enhanced PVD-based steganography system that incorporates a dynamic programming approach to optimise the embedding process. By dynamically selecting pairs of pixels and allocating data optimally, it improves the trade-off between image distortion and embedding capacity. Additionally, an extra layer of security is implemented using a Rubik’s Cube scrambling algorithm that rearranges the pixels in the stego image. This hybridisation of PVD optimisation with scrambling ensures that even when a stego image is successfully obtained, extracting the hidden data becomes significantly more challenging. Our approach demonstrates superior image quality and robustness against steganalysis, providing a secure and efficient method for covert communication.

Keywords: Pixel Value Differencing (PVD); Image Steganography; Visual Invisibility; Data Embedding Optimization; Steganalysis Resistance; PVD Optimization; Steganography System.

Received on: 10/09/2024, Revised on: 13/11/2024, Accepted on: 16/12/2024, Published on: 03/06/2025

DOI: 10.69888/FTSCL.2025.000422

FMDB Transactions on Sustainable Computer Letters, 2025 Vol. 3 No. 2, Pages: 60-75

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