Development of Stegano – Visual Cryptography Technique using GWO-CSA-Based Novel Hybrid Heuristic Algorithms

Abstract

Steganography is used to convey information that is concealed behind another, more evident message, protecting the information in the process. Sensitive data is embedded into cover material as a way of data obfuscation. Nowadays, text, picture, audio, and video steganography can be used to hide information. Multimedia steganography is a very secure steganography because concealed messages are contained in the noisy files' lowest-valued bits. While cryptography frequently encodes signals to ensure they are not readily understood, steganography obscures data in a way that it cannot be easily viewed. Visual cryptography (VC) is a way of encoding that makes it possible for visuals to only be decrypted by the human visual system. Color composition, color palette sorting, understanding the relationships between various color indices, exaggerated noise, and brightness are some steganography techniques. To enhance the message size when using the Joint Quantization Table Modification (JQTM), approach, a novel steganography methodology based on Cuckoo Search (CS) hybridized with Grey Wolf Optimizer (GWO) has been introduced. The approach was primarily inspired by the optimum LSB substitution methodology, which first transforms any secret message through an optimal matrix of replacement and then produces cover images. Since the replacement approach enhances the stego-image value within a spatial domain, it may be utilized in conjunction with the frequency domain method. In the suggested hybrid CS-GWO, the GWO search area has been increased, and the GWO local optima problem is avoided. CS excels at solving global optimization issues because it can balance local and global random walks utilizing switching parameters. The findings show that the recommended CS-GWO has a bigger capacity than CSO.