A recent approach based on inspired crows behavior in steganography

Abstract

Nowadays, preventing data transmission via networks from unauthorized access has become crucial. In this work, we introduce a new enhanced Crow Search Algorithm (CSA), named NECSA, for solving the search problem. Then, we propose a steganographic approach called Steganographic NECSA (SNECSA). It is based on NECSA for obtaining optimal positions and the Least Significant Bit (LSB) method for concealing secret data in these positions. For gray-scale images, SNECSA is applied with 4-LSB. For colored images, SNECSA is applied in two versions. The first one uses 3–3–2 LSB, while the other uses 3–3–2 LSB and permutations on each secret byte, obtaining six patterns and choosing the fittest pattern to embed. The practical results show that the proposed approach outperforms other previous approaches with respect to peak signal to noise ratio, bit error rate, and number of pixel change, where the average peak signal to noise ratios achieved by the proposed approach are approximately 76.25 dB, 73.47 dB, and 71 dB in gray-scale images, and 83.76 dB, 80.9 dB, and 78.7 dB in color images on the tested data set. Additionally, the suggested approach shows outstanding resistance to stego-attacks such as salt and paper noise and regular and singular analysis.