Secure Audio Embedding in Images using Nature-Inspired Optimization

TL;DR

The paper tackles secure audio hiding in images by optimizing LSB embedding with Harris Hawks Optimization. It introduces a pipeline that preprocesses audio into a bitstream, uses HHO to select pixel locations based on a SSIM-PSNR fitness, and performs adaptive LSB embedding in high-variance image blocks. Experimental results show PSNR above 55 dB and SSIM around 0.999, with rapid convergence (≈200 iterations) and superiority over other metaheuristics like FA and CS. The approach achieves imperceptible, robust, and efficient audio steganography suitable for practical use.

Abstract

In todays digital world, protecting sensitive data is very essential. Steganography hides the existence of secret data instead of its content, providing better security for multimedia communication. This paper proposes a new technique for hiding audio files inside images using the Least Significant Bit (LSB) method optimized by the Harris Hawks Optimization (HHO) algorithm. HHO is a nature-inspired metaheuristic that imitates the hunting behavior of Harris hawks to find optimal pixel positions for embedding data. The proposed method is evaluated using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Mean Square Error (MSE). Experimental results show that HHO achieves better image quality, robustness, and embedding capacity compared to existing methods.

Figures (2)

• Figure 1: Block diagram of Proposed Method
• Figure 2: Harris Hawks optimization steg results are shown in images a,b,c,d,e above