Optimized Data Hiding Technique Using Egyptian Vulture Optimization Algorithm For Image Steganography

Abstract

Image steganography algorithms have been used extensively for securing sensitive data by hiding it in the cover image. One of the most preferred algorithms for securing the sensitive information is least significant bit (LSB) where a secret data bit usually replaces the least significant bit in the cover image pixel. However, the data hiding process can degrade the image quality and finds attention of an attacker. For enhancing the quality of a cover image, various optimization algorithms have been utilized but there is a need to explore the optimal starting pixel in the cover image for data hiding. Therefore, in this paper, an optimized data hiding technique has been proposed that can quickly explore the optimal starting pixel in the cover image for data hiding. This can be achieved by using an Egyptian Vulture Optimization (EVO) algorithm where three operations are performed in different iterations for determining an optimal solution based on the fitness function. To validate the performance of the suggested technique, simulation results are performed on standard dataset images. The performance of the proposed technique is evaluated against the popular optimization-based data hiding algorithms. It is established that proposed technique is superior in terms of PSNR. Additionally, the secret data can be hidden in original or transform form. Thus, the recovery of secret is impossible in the receiver side until its data form is not identified. The proposed technique is useful in image steganography as it allows the user to quickly explore the optimal starting pixel in the cover image.