An Efficient Steganography Method Using Advance PVD
ABSTRACT:
This paper proposes a high capacity data hiding method using modulus function of pixel-value differencing (PVD) and least significant bit (LSB) replacement method. Many novel data hiding methods based on LSB and PVD methods were presented to enlarge hiding capacity and provide an imperceptible quality. A small difference value for two consecutive pixels is belonged to a smooth area and a large difference one is located on an edge area. In our proposed method, the secret data are hidden on the smooth area by the LSB substitution method and PVD method on the edge area. From the experimental results, the proposed method sustains a higher capacity and still a good quality compared with other LSB and modified PVD methods.
EXISTING SYSTEM:
The least-significant-bit (LSB)-based approach is a popular type of steganographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover image mainly depends on a pseudorandom number generator without considering the relationship between the image content itself and the size of the secret message. Thus the smooth/flat regions in the cover images will inevitably be contaminated after data hiding even at a low embedding rate, and this will lead to poor visual quality and low security based on our analysis and extensive experiments, especially for those images with many smooth regions. Steganographic method based on least-significant-bit (LSB) replacement and pixel-value differencing (PVD) method is presented. First, a different value from two consecutive pixels by utilising the PVD method is obtained. A small difference value can be located on a smooth area and the large one is located on an edged area. In the smooth areas, the secret data is hidden into the cover image by LSB method while using the PVD method in the edged areas. Because the range width is variable, and the area in which the secret data is concealed by LSB or PVD method are hard to guess. To estimate how many secret bits will be embedded into the two pixels. Pixels located in the edge areas are embedded by a k-bit LSB substitution method with a larger value of k than that of the pixels located in smooth areas. The range of difference values is adaptively divided into lower level, middle level, and higher level. For any pair of consecutive pixels, both pixels are embedded by the k-bit LSB substitution method. However, the value k is adaptive and is decided by the level which the difference value belongs to. Most existing steganographic approaches usually assume that the LSB of natural covers is insignificant and random enough, and thus those pixels/pixel pairs for data hiding can be selected freely using a PRNG. However, such an assumption is not al-ways true, especially for images with many smooth regions.
PROPOSED SYSTEM:
In this paper, we consider dig-ital images as covers and investigate an adaptive and secure data hiding scheme in the spatial least-significant-bit (LSB) domain. LSB replacement is a well-known steganographic method. In this embedding scheme, only the LSB plane of the cover image is overwritten with the secret bit stream according to a pseuo random number generator (PRNG). As a result, somestructural asymmetry (never decreasing even pixels and increasing odd pixels when hiding the data) is introduced, and thus it is very easy to detect the existence of hidden message even at a low em-bedding rate using some reported steganalytic algorithms, such as the Chi-squared attack, regular/singular groups (RS) analysis , sample pair analysis, and the general framework for structural steganalysis.This paper presents a novel steganographic algorithm based on the spatial domain: Selected least Significant Bits (SLSB). It works with the least significant bits of one of the pixel color components in the image and changes them according to the message’s bits to hide. The rest of bits in the pixel color component selected are also changed in order get the nearest color to the original one in the scale of colors. This new method has been compared with others that work in the spatial domain and the great difference is the fact that the LSBs bits of every pixel color component are not used to embed the message, just those from pixel color component selected.
ALGORITHM:
Least Significant Bit (LSB)
image file using Least Significant Bit (LSB) technique. The LSB algorithm is implemented in spatial domain in which the. payload bits are embedded into the least significant bits of cover image to derive the stego-image.The Least Significant Bit (LSB) is one of the main techniques in spatial domain image Steganography. The LSB is the lowest significant bit in the byte value of the image pixel. The LSB based image steganography embeds the secret in the least significant bits of pixel values of the cover image (CVR).Sometimes abbreviated as LSB, the least significant bit is the lowest bit in a series of numbers in binary; the LSB is located at the far right of a string. For example, in the binary number 10111001, the least significant bit is the far right 1
MODULES:
1, Enter Secret Message
STEGANOGRAPHY is a technique for information hiding. It aims to embed secret data into a digital cover media, such as digital audio, image, video, etc. We can use digital images, videos, sound files, and other computer files that contain perceptually irrelevant or redundant information as covers or carriers to hide secret messages. After embedding a secret message into the cover image, we obtain a so-called stego-image..
2. Decryption Image
A small difference value can be located on a smooth area and the large one is located on an edged area. In the smooth areas, the secret data is hidden into the cover image by LSB method while using the PVD method in the edged areas. Because the range width is variable, and the area in which the secret data is concealed by LSB or PVD method are hard to guess.
3. Encryption Image
This paper presents a novel steganographic algorithm based on the spatial domain: Selected least Significant Bits (SLSB). It works with the least significant bits of one of the pixel color components in the image and changes them according to the message’s bits to hide. The rest of bits in the pixel color component selected are also changed in order get the nearest color to the original one in the scale of colors.
4. Show Secret Message
The least-significant-bit (LSB)-based approach is a popular type of steganographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover image mainly depends on a pseudorandom number generator without considering the relationship between the image content itself and the size of the secret message
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