Hiding data inside images using orthogonal moments

TL;DR

This paper introduces a novel steganographic method that embeds secret messages into high-frequency image coefficients using orthogonal moments, chaotic maps, and AES-based key expansion to enhance security and imperceptibility.

Contribution

The paper presents a new steganography technique combining orthogonal moments, chaotic maps, and AES-derived keys for improved security and image quality.

Findings

Enhanced imperceptibility demonstrated by higher PSNR values.

Improved security indicated by increased Relative Entropy.

Effective embedding in high-frequency coefficients with minimal image distortion.

Abstract

In this contribution we propose a novel steganographic method based on several orthogonal polynomials and their combinations. The steganographic algorithm embeds a secrete message at the first eight coefficients of high frequency image. Moreover, this embedding method uses the Beta chaotic map to determine the order of the blocks where the secret bits will be inserted. In addition, from a 128-bit private key and the steps of a cryptography algorithm according to the Advanced Encryption Standard (AES) to generate the key expansion, the proposed method generates a key expansion of 2560 bits, with the purpose to permute the first eight coefficients of high frequency before the insertion. The insertion takes eventually place at the first eight high frequency coefficients in the transformed orthogonal moments domain. Before the insertion of the message the image undergoes a series of transformations. After the insertion the inverse transformations are applied to the original transformations in reverse order. The experimental work on the validation of the algorithm consists of the calculation of the Peak Signal-to-Noise Ratio (PSNR), the Universal Image Quality Index (UIQI), the Image Fidelity (IF), and the Relative Entropy (RE), comparing the same characteristics for the cover and stego image. The proposed algorithm improves the level of imperceptibility and security analyzed through the PSNR and RE values, respectively.