Sleuthing images that conceal information has continuously been a stimulating and difficult problem in cyber security. Finding hidden data in nursing image is called steganalysis. In this chapter, the authors explore the method employed in the study. The investigational results are have included followed by a discussion with prospect analysis. Several 2×2 blocks are recycled to implant the data bits within the stego-image, and using the Arnold Map, four quadrants of the pixels of each block is selected to embed the data in nonlinear bit position. Different measures with the change of BPP (bits per pixel) are also worked out.
Top1. Introduction
With the progress of computer machinery in current years, information security is considered as one of the significant features in imminent information and communication technology. Cyber security has also become a trending security aspect in current days. Therefore, it’s essential to take crucial measures to protect the confidential information. As a whole, confidential information can be secure by prevalent of two ways: by encryption or steganography. Cryptography encrypts stealthy messages to make them incomprehensible i.e. the encrypted message is visible to us but it’s unexplainable to us. While steganography secrets the existence of the message through the carrier i.e. it covers the existence of secret messages (Setiadi, 2022).
Presently several methodologies that exist for finding of such concealed data bits within the form of information or images that largely need corporal inspection. During this model, some sensitive data has been embedded within Associate in nursing image, referred to as the stego-image and with none loss, extract constant data from that image, called the cover image(Rabie, 2021).
Steganography stands for the cleverness of concealing evidence in such a way that it prevent the uncovering of stealthy communications. It’s originate from the Greek term for “covered writing”. It comprises a variety of dissimilar secret communication methodologies that conceal the existence of unrevealed messages. Steganography are classified into different types like, Text Steganography, Image Steganography, Audio Steganography, Video Steganography and Protocol Steganography. The image encryption method is utmost of the active ways to protect our privacy. The process of hiding a secret message inside the image has become widely used, due to weaknesses in the Human Visual System (HVS), as well as due to the reduced cost of storing and communicating the image (Subramanian et al., 2021; Wang, 2022).
Imaging steganography techniques can be divided into two cluster: Transform Domain and Spatial Domain Technique. The Transform domain technique embeds information into the frequency domain of the previously transformed image, while the spatial domain technique embeds the information directly into the pixel intensity (Ali et al., 2021). The spatial domain embedding technique is very common and informal to us in the field of steganography.
In terms of image hiding, we have noted that the original image without the secret message embedded is called the cover image or the carrier image, while the image resulting from the embedding of the secret message. The secret is called the hidden image. The secret message can be in the form of text, images, audio or video. After applying the steganography method, the output stego-image generated will look like the cover image.
There are reciprocal relationships between the requirements of cryptographic printing: capacity, robustness, and insensitivity (as in Fig. 1). Robustness refers to how much stego-image spoofing can withstand that an attacker cannot detect hidden data bits. Capacity indicates the volume of data bits that can be embedded in the cover medium lacking of damaging the integrity of the shield image. The most important requirement of a cryptographic recording system is insensitivity, since the strength of a cryptographic copy system dishonesties in its ability to remain ignored by human senses (like visual or audible). How to poise this three necessities in the fields of information hiding is an interesting question in current years (Sharmin et al., 2019; Kadhim, 2019).
Figure 1. Triangle model of steganography