LSBs Steganography Based on R-Indicator

Abstract

Steganography is the art and science of hiding secret data inside other data called the cover data. This makes it hard to detect the existence of the secret data by third parties. There are different models of carrier that can be used as stego cover, such as text, image, audio and video to hide information. The most common way is the image due to the reluctance on the internet. And thus it can guarantee a high degree of security. There are a lot of algorithms and techniques to hide data. Every algorithm has its own mechanism which has strengths and weaknesses points. Some techniques are limited with hiding inside specific type of data, and some can be used with multiple types of carriers. This study introduces a new algorithm called ST_R-indicator steganography algorithm for hiding data based on the Least Significant Bit (LSB), where the algorithm embeds inside these LSB(s). The researcher proposed a new algorithm that used benchmark RGB images (with png, bmp extention) as a cover media where each pixel is represented by three bytes (24 bit) red, green, and blue in pixel. The process of hiding depends on pixel indicator technique which is called R-indicator. They use the same principle of the Least Significant Bit (LSB), where the secret message is hidden at the least significant bits of the pixels, with more randomization in chosen of the number of bits used and the colour channels that are used. In addition, they may be embedded into one or two bits at the same time. This randomization makes the method robust against steganalysis and this is the advantage of this algorithm over normal LSB algorithm and also increases the capacity of information. After completing implementation of the proposed algorithm, the researcher evaluated the proposed algorithm to measure its efficiency in aspects of imperceptibility, capacity, robust and ranomaization. Many tools were used such as PSNR, MSE, StegExpose and histogram. Experimental results showed an increasement capacity of information, increasing robust and better image quality. Its notability was compared to several existing methods.