Role of Bioinspired Optimization Algorithms in Medical Image Steganography for Healthcare Applications

Abstract

Steganography is the practice of hiding one piece of information within another, and in the context of medical images, it involves concealing sensitive patient data within the images for secure transmission and storage. Bioinspired algorithms play a significant role in medical image steganography for healthcare applications. They may be used to design complex encryption and embedding schemes that are difficult for unauthorized users to break. These algorithms mimic the robustness of biological systems against various attacks. They can be employed to find the best locations within the medical images to hide data while minimizing the impact on image quality. Bioinspired algorithms, such as genetic algorithms or swarm intelligence, are also used to create adaptive systems that optimize the embedding process according to specific criteria. Bioinspired algorithms may be designed to ensure that the hidden data remains robust even when the images are subjected to compression or noise reduction processes. This enhances the reliability of the steganography technique in practical healthcare scenarios. Bioinspired algorithms can be optimized for speed and efficiency, enabling rapid embedding and extraction of data from medical images without significant delays. In this chapter, the authors do a comparative study of the various bioinspired algorithms for medical image steganography.