Abstract
Classic Least Significant Bit (LSB) steganography technique is the most used technique to hide secret information in the least significant bit of the pixels in the stego-image. This paper proposed a technique by splitting the secret message into set of segments, that have same length (number of characters), and find the best LSBs of pixels in the stego-image that are matched to each segment. The main goal of this technique is to minimize the number of LSBs that are changed when substituting them with the bits of characters in the secret message. This will lead to decrease the distortion (noise) that is occurred in the pixels of the stego-image and as result increase the immunity of the stego-image against the visual attack. The experiment shows that the proposed technique gives good enhancement to the Classic Least Significant Bit (LSB) technique.
Highlights
Steganography is one of many techniques that are used to hide secret information to prevent any attackers to make damage in this information or use it in illegal form
To clarify the effect of SegmentLength on the performance of the proposed Segmented-Least Significant Bit (LSB) image steganography technique, different selected values of the SegmentLength used on the above experiments
When increase the SegmentLength the Signal to Noise Ratio (SNR) will decrease and vice versa. This is because the value of SNR of the stego-image is proportional with the number of LSB that are changed in the pixels of the stego-image
Summary
Steganography is one of many techniques that are used to hide secret information to prevent any attackers to make damage in this information or use it in illegal form. Cryptography is used for the same purpose but steganography is more widely used technique as it hides the existence of secret data Another application of steganography is feature tagging. The idea in this paper is that when substitute the LSB of the pixels (in the stego-image) with the bits of all characters (in the secret message) as one segment, this will result a large number of changes that are happen in LSB of pixels. When the proposed technique split the long secret message into number of small segments, this will lead to increase the probability of finding best matching between the bits of the characters in the secret message and the LSB of the pixels in the stego-image. As a result of that, the distortion/noise that will appear in the pixels of the stego-image will be decrease and the immunity of the stego-image against the attack by human visual system (HVS) becomes strong
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