Abstract:

Sensitive data has frequently been secured using picture steganography techniques by concealing it in the cover image. Least Significant Bit (LSB), which substitutes a secret data bit for the least significant bit in the cover picture pixel, is one of the most popular techniques for protecting sensitive information. The data concealment technique, however, can reduce the image’s quality and draw an attacker’s notice. Numerous optimization algorithms have been used to improve cover picture quality, but more research is needed to determine the best cover image pixel from which to conceal data. The best beginning pixel in the cover image for data concealing has thus been quickly explored using an efficient data hiding technique that has been proposed in this paper. The Egyptian Vulture Optimization (EVO) algorithm, which performs three operations in various iterations to find the best solution based on the fitness function, can be used to do this. Images from a typical dataset are used in the simulation results to verify the suggested technique’s effectiveness. The effectiveness of the suggested method is assessed in comparison to well-known optimization-based data concealment strategies. It has been proven that the proposed technique offers a higher PSNR. The secret data can also be concealed in its original or transformed form. As a result, while its data form is unknown, the receiving side cannot retrieve the secret. The suggested method helps with image steganography since it makes it simple for the user to find the best starting pixel in the cover image.

Keywords: Steganography, LSB, Security, Egyptian Vulture Optimization.