Secure Audio Embedding in Images using Nature-Inspired Optimization

TL;DR

This paper introduces a steganography technique that embeds audio in images using LSB optimized by Harris Hawks Optimization, enhancing security, image quality, and robustness over existing methods.

Contribution

It presents a novel HHO-based optimization for LSB steganography, improving embedding capacity and image quality in audio-in-image hiding.

Findings

HHO improves PSNR, SSIM, and MSE metrics.

The method enhances robustness against detection.

It achieves higher embedding capacity.

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.