ABSTRACT
The growing demand to protect the confidential messages and documents paved way for the invent of information security techniques. Whatever, be the strength of security algorithms and standards, an equal amount or greater than that attempt is made to crack the information which employs an algorithm to make it invisible to anonymous. New techniques and algorithms will help a lot for strengthening the security of our information systems. Steganography is basically a science turned art to hide the payload with the help of a carrier. We propose a spatial domain image steganography technique which uses two aspects for information hiding-one being the pixel nibble difference and the other in the form of block rotation decided by a variable P. This technique adds a technique to the group of information hiding techniques where block rotation can be decided by various parameters concerned with the carrier which may be audio, video or text.
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DOI: 10.3923/itj.2014.2005.2010
URL: https://scialert.net/abstract/?doi=itj.2014.2005.2010
INTRODUCTION
The radical change in information handling has been enhanced by the kind of information security methodologies (Al-Azawi and Fadhil, 2010; Al-Frajat et al., 2010; Amirtharajan and Balaguru, 2009; Amirtharajan and Rayappan, 2012a-d; Amirtharajan et al., 2011) which have been developed over the years. The present internet world works with enormous payload but protection of the payload till it reaches out the concerned is a big challenge (Cheddad et al., 2010; Amirtharajan et al., 2012). We have come across security approaches broadly classified into three. Cryptography (Schneier, 2007), a technique which scrambles the payload with the help of a key to make the payload or data, known to be cipher text. Public Key, Private Key, Block Ciphers, Stream Ciphers and Encryption standards proposed by Forensic agencies are a part of cryptography family. On the other hand, Information copy right protection is achieved through watermarking (Karzenbeisser and Perircolas, 2000; Zeki et al., 2011). Robust and Fragile are the predominantly used categories of watermarking.
Steganography, the third approach is a methodology to hide the secret message in a carrier which is also called cover (Cheddad et al., 2010; Hmood et al., 2010a, b; Amirtharajan and Balaguru, 2009; Amirtharajan and Rayappan, 2012a-d; Amirtharajan et al., 2011). The cover for carrying or hiding the information may be an image, audio file (Zhu et al., 2011) or a video file (Al-Frajat et al., 2010). Steganography on image has been reported in various earlier works (Janakiraman et al., 2012a, b; Thanikaiselvan et al., 2011a, b). Various parameters have been considered in the past such as methods to decide the amount of information to be hidden (ie) capacity, Increasing the robustness of hiding process, Encryption hiding on image, Image processing based hiding techniques, Adaptive embedding, Integrity check mechanism added stegano approach (Amirtharajan et al., 2011), Random pixel embedding, Block based emedding etc., Also FPGA based steganography approaches (Rajagopalan et al., 2012a, b) have been reported in literature.
Simple LSB substitution with optimal pixel adjustment process, fondly called as OPAP has been proposed by Chan and Cheng (2004). Pixel value differencing is proposed by Wu and Tsai (2003) where number of bits embedded is decided by the proposed algorithm. Hiding information on RGB images have been presented by Amirtharajan and Balaguru (2009) and Amirtharajan et al. (2011) and many other works (Padmaa et al., 2011; Mohammad et al., 2011; Thenmozhi et al., 2012; Qi et al., 2010; Zaidan et al., 2010; Zanganeh and Ibrahim, 2011).
We propose a grayscale image steganographic algorithm which uses nibble differencing technique where minimum absolute difference between the Upper nibble of the pixels of a selected 2x2 message embedded image block guides the block bits rotation angle to make the final stego image.
PROPOSED METHODOLOGY
Let I be the grayscale image with Ax and By as its row and column dimensions, where 1≤x≤N and 1≤y≤N. Here, Ixy is an element of the image I.
When a message mj from the {M} has to be embedded into a pixel Ixy, the pixel undergoes the following change:
Ixy = Ixy-Ixy mod 2k + mj
where, k is the No. of bits to be embedded in a pixel Ixy. Grayscale Image of size NxN I is divided into blocks such that:
Ibmn ∈ I | Ib⊂I
where 1≤m≤2 and 1≤n≤2. Figure 1 shows the Ib subset.
Now Ib is a subset of I (ie) a 2x2 pixel group which belongs to the grayscale image I. Let us assume the Ib with the following elements:
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where, i and j are row and column respectively. After embedding encrypted k-bits in the Ib block, the block becomes:
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Let this embedded block be an intermediate block Intb.
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Fig. 1: | Subblock Ib from the Image I |
Calculating the absolute differences between Upper nibble of the Intb block pixels:
• | D1 = abs ((Ibi,j-1>>4)-(Ibi,j>>4)) |
• | D2 = abs ((Ibi,j-1>>4)-(Ibi-1,j-1>>4)) |
• | D3 = abs ((Ibi,j-1>>4)-(Ibi-1,j>>4)) |
• | D4 = abs ((Ibi,j>>4)-(Ibi-1,j-1>>4)) |
• | D5 = abs ((Ibi,j>>4)-(Ibi-1,j>>4)) |
• | D6 = abs ((Ibi-1,j-1>>4)-(Ibi-1,j>>4)) |
where, {D1,D2,D3,D4,D5,D6} ∈ {D}. Finding minimum ({D}) which is the minimum difference between a pair of pixels of the block and {el(minimum({D})}, which is the pair of nibbles producing minimum difference to decide the number of times the embedded k-bits of all the pixels of the block has to be rotated. By concatenating upper nibbles of {el} by doing the following operation we get:
P = ((el1 ∈{el}) & 240) OR (el2 ∈{el}) >> 4
where, P gives a number of times the lower nibbles of the block has to be rotated. The 6th bit b6 of P decides the direction in which the rotation should happen:
• | If b6 is 1_Clockwise Embedded k-bits rotation P times |
• | If b6 is 0_Anti-clockwise Embedded k-bits rotation P times |
P can also be expressed as:
P = (((el1 ∈{el}) & 240) OR (el2 ∈{el})>> 4) mod 4
Because if block is rotated 4 times, the resultant block will be equal to the Intermediate block and also one time rotation of the block clockwise or anticlockwise results in change in orientation of the block by 90°. This holds good for even 1 bit rotation among the pixels of the block.
Therefore P times rotation = (P mod 4) times rotation. Figure 2 shows the orientation of the Intermediate block Intb after various rotation angles.
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Fig. 2(a-d): | (a) Intermediate block, (b) 90° clockwise lower nibble rotation (c) 180° clockwise lower nibble rotation and (d) 270° clockwise lower nibble rotation |
Here, Ibi-1,j-1 = (Ibi,j-1 & 240) OR (Ibi-1,j-1 & 15), if k = 4. Similarly other elements of Ib can be computed for different k values.
After rotation, the procedure has to be repeated for other Ib blocks by selecting the blocks in a random manner or by a specific order defined by the user.
Let us consider an example. Let Ib be:
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A total number of 16 bits have to be embedded in this block. The encrypted message to be embedded is 0000111100001111. It is evident that each pixel should carry 4 bits of secret information making k = 4. After embedding the secret message the Ib becomes:
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When finding the {D}, the elements of {D} are D1 = 0, D2 = 1, D3 = 1, D4 = 1, D 5 = 1 and D6 = 0. As the minimum of {D} are D1 and D6 and considering the difference pair based on the order of precedence which is D1, {el} elements are 144 and 159. Concatenating the upper nibbles of 144 and 159 we get P as 100110012 which is equivalent to 153 in decimal. As b6 of P is 0, 153 times Anticlockwise rotation or P = 153 mod 4 (ie) 90° anticlockwise rotation (or) one time block rotation by left. Now the resulting block will be:
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The decryption of message from the stego image can be done as per the following pseudo code:
For I = 1: Total blocks |
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RESULTS AND DISCUSSION
The algorithm has been tested on various grayscale images of size 256x256 using LabVIEW software with IMAQ tool box. Four images namely Cameraman, Vegetables, Mahathma Gandhiji and Sailboat were used for testing our hiding method. Figure 3(a-d) show the cover images considered and Fig. 4(a-d) display the stego images for k = 1, 2,3 and 4.
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Fig. 3(a-d): | Cover images (a) Cameraman, (b) Vegetables, (c) Mahathma Gandhiji and (d) Sail Boat |
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Fig. 4(a-d): | Stego images (a) Cameraman (k = 1), (b) Vegetables (k = 2), (c) Mahathma Gandhiji (k = 3) and (d) Sailboat (k = 4) |
Table 1: | MSE results for various K values |
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Table 2: | PSNR results for various K values |
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The quality of the stego images after embedding secret data in the cover images has been computed with parameters like Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). Table 1 presents the MSE and Table 2 presents the PSNR for the test images with different k-bit embedding.
The Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) of a received stego image can be calculated as follows:
![]() |
where, X and Y are image coordinates, M and N are the dimensions of the image. SXY is the message containing stego-image and CXY is the cover image. Also S2max has the maximum intensity value in the image which is 255 for the grayscale images.
COMPLEXITY AND ROTATION STATISTICS OF STEGO ALGORITHM
The complexity of this algorithm can be analysed as follows:
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Fig. 5: | Rotation statistics for various test images |
We have considered 256x256 grayscale images that contain 16384 2x2 blocks. The order of choosing the 2x2 blocks can be done in 16384! ways. For full capacity embedding, as per the worst case PSNR, each pixel can carry 4 bits which means a 2x2 block needs 16 bits. This 16 bit message can be scrambled in 16! ways. The arrangement of 4bits message/pixel for a 2x2 block can be done in 4! ways. Also the block can be rotated in 4 different ways.
Therefore, the total complexity of the system is 16384! x16!x4!x4.
The theoretical probability of rotating the block by specific angle from angle set {0, 90, 180, 270°} ∈ {A} is ¼. We have done an analysis on the probability of rotating a block by a specific angle from the {A} by computing, of the 16384 2x2 blocks of 256x256 stego image how many blocks are rotated by an angle from {A} and this analysis is shown in the graph displayed in Fig. 5.
It is inferred from the Fig. 5 that comparatively lesser number of blocks were not rotated (ie) number of blocks rotated by 0 or 360° is less. As per this analysis, the average probability of rotating a block by 0° is 0.218201, 90° is 0.235138, 180° is 0.287048 and that of 270° is 0.259613. Comparing this with theoretical probability of block rotation, 0° and 90° fell short of ¼ threshold.
CONCLUSION
A gray image steganographic algorithm with block rotation has been proposed in this paper. Nibble differencing has been the key to decide block rotation and this approach has resulted in distributed angle rotation. This approach has also yielded approximately 78.17% of total 16384 blocks being rotated by non-zero angle. Also the stego images generated by our algorithm has an excellent imperceptibility being supported by the PSNR and MSE results of various test images. This technique can also be coupled with other stegano approaches like transform domain steganography.
ACKNOWLEDGMENT
The authors wish to express their sincere thanks to DRDO, New Delhi for their financial support (ERIP/ER/1003836/M/01/1230). They also wish to acknowledge SASTRA University, Thanjavur for extending infrastructural support to carry out the study.
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