Ijett v7p224

International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014

A Pragmatic Approach in Lossless Data Hiding for JPEG Images T. S.Sandeep 1#

#1

, J. Shankar babu *2, Dr.N. Sudhakar Reddy@3

Assistant Professor, Dept of CSE,SVEW, TIRUPATI, AP, India Associate Professor, Dept of CSE,SVEW,TIRUPATI, AP, India 3@ PRINCIPAL, SVCE, TIRUPATI, AP, India

2*

Abstract— In this paper Reversible Data hiding restores

the carrier once the removing hidden secret information.

Many reversible data hiding techniques were proposed within the past few years, but on analysis, almost all does not have in providing the security and authentication. This paper proposes a novel reversible data hiding technique which effort is separable, the receiver can extract the initial image or additional embedded information or both based on the keys hold from the receiver. Alternatively the receiver can verify the information hided through the data hider, so that the work proposes both security and authentication. Digital steganography and watermarking are both types of information hiding. Digital watermarking usually mentioned as hiding for comforting the data. Information hiding in image process could occur the long term frame distortions and then the initial cover medium is probably not prepared to be turned around precisely, once the hidden knowledge are extracted out.

This work proposes a novel scheme for separable reversible data hiding in encrypted images. Within the first phase, a content owner encrypts the initial uncompressed image having an encryption key. Then, a data-hider may compress minimal significant bits of the encrypted image by using a data-hiding step to produce a sparse space to allow for some additional data. Through an encrypted image containing additional data, if the receiver gets the data-hiding key, he is able to extract the additional data though he doesn't be aware of image content. When the receiver contains the encryption key, they can decrypt the received data to acquire an image just like the original one, but cannot extract the additional data.

Keywords: Reversible Data Hiding, Histogram, Stenography, Performance, Watermarking.

I. INTRODUCTION In an interactive buyer–seller protocol for invisible watermarking, the seller does not know the exact watermarked copy that the buyer receives. So the seller cannot create copies of the original content containing the buyer’s watermark. If

ISSN: 2231-5381

the seller finds an unauthorized copy, the seller can identify the buyer from the watermark using the unauthorized copy, and hence the seller can prove this fact to a third party using a dispute resolution protocol. In it is desired to transmit redundant data over an insecure and bandwidth-constrained channel, it is desired to first compress the data and then encrypts it. Traditional techniques used to compress the data first and then encrypt the data.

But we are reversing the order of these steps, thereby first encrypting and then compressing the data. A significant compression ratio can be achieved if compression is Performed after encryption. Compression is performed by standard source code and decryption by decompression.

Data hiding is referred to as a process to hide data into cover media. This implies that the data hiding process links two sets of data, a set of embedded data and another set of cover media data. These two sets of data have different applications. In covert communications, the hidden data may often be irrelevant to the cover media. In authentication, the embedded data is closely related to the cover media. In these two types of applications, the invisibility of hidden data is an important factor. In some cases of data hiding, the cover media will experience some distortion due to data hiding and cannot be inverted back to original media. That is, some permanent distortion has occurred to the cover media even after the hidden data have been extracted out. In other applications, such as remote sensing and high-energy particle physical experimental analysis, it is also desired that the original cover media can be recovered because of the required high-precision. In addition, information sharing was proposed to protect the security of concerned data by transforming a secret message into several shares which are then distributed to a number of participants to keep. Such a secret sharing scheme is useful for reducing the risk of incidental data loss and advantageous for keeping a balance among the participants: only when all the shares or a sufficient number of them are collected from the participants can the secret message be recovered correctly. This concept of secret sharing.

Conventionally, data hiding and information sharing are two irrelevant issues in the domain of information security. In this study, a new data hiding method based on the technique of

http://www.ijettjournal.org

Page 26

International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014 information sharing is proposed for hiding data into PNG (portable network graphics) images.

The reversible data hiding in encrypted image is investigated, most of the work on reversible data hiding focuses on the data embedding/extracting on the plain spatial domain But, in some applications, an inferior assistant or a channel administrator hopes to append some additional message, such as the origin information, image notation or authentication data, within the encrypted image though he does not know the original image content. And it is also hopeful that the original content should be recovered without any error after image decryption and message extraction at receiver side. The presents a practical scheme satisfying the above-mentioned requirements and Fig. 1 gives the sketch. A content owner encrypts the original image using an encryption key, and a data-hider can embed additional data into the encrypted image using a data-hiding key though he does not know the original content. With an encrypted image containing additional data, a receiver may first decrypt it according to the encryption key, and then extract the embedded data and recover the original image according to the data-hiding key. In the scheme, the data extraction is not separable from the content.

II. LITERATURE SURVEY In the literature, many data hiding methods exploring the spatial domain and Frequency domain of images has been proposed. Bender et al. [12] proposed The technique of leastsignificant-bit (LSB) replacement, in which a secret message is embedded in the least significant bits of image pixel values.

Mielikainen [13] Proposed a modified LSB replacement method which embeds as many bits as the Conventional method, but changes less pixel values. Yang et al. [14] proposed an Adaptive k-LSB substitution method in which larger values of k are adopted in the Edge areas of the cover image and smaller ones are used for the smooth areas. Wang et al. [15] transformed image block contents into coefficients in the frequency domain By the discrete cosine transform (DCT) and embedded secret bits by modifying the Magnitude relations between the AC values of image blocks. Besides data embedding Techniques using the DCT, the discrete wavelet transform (DWT) [17] and the discrete Fourier transform (DFT) [18-19] have also been used.

From another viewpoint, different types of images and files can be used as cover Media for developing data hiding [2021]. In [21], Lee and Wu proposed a lossless Data hiding method for palette-based images, which adjusts palette colors and image Data to embed secret data and side information for reconstruction of the original Image content. Lee and Tsai [9] hid data into PDF files’ characters by using special ASCII codes. Liu [10] made use of the change tracking function in Microsoft Word to Hide data by a document degeneration technique.

ISSN: 2231-5381

In this paper, in addition to the aforementioned spatial domain, frequency Domain and palettes of images for use in data hiding, we try to explore a new Embeddable space for data hiding, aiming at providing more data hiding capacity, Better quality of the resulting stego-image and stronger applicability. As a result, the PNG image with the alpha channel plane is found to be capable of meeting these Requirements mentioned previously. Specifically, in the information-sharing-based Data hiding method proposed in this study, a PNG image is used as the cover image in Which the alpha-channel value of each pixel is set to be 255 initially.

In recent years, several researchers have revealed a large form of image data hiding techniques in the literatures.

These techniques are often classified roughly into 3 approaches, i.e., the spatial domain, the frequency domain, and also the compression domain. Within the spatial domain, the cover image is altered directly and undetectably to hide the secret message. Lee and Chen [18] proposed a steganographic algorithm applied within the spatial domain during which the smallest amount important bit (LSB) of every pixel within the cover image was replaced by secret data. Later, Chang et al.

[19] found the best LSB substitution for embedding secret data by using a dynamic programming strategy. By applying each run-length coding and standard computation, Chang et al.

[20] designed 2 efficient data hiding ways for icon files and grayscale files. The entire on top of ways is irreversible data hiding schemes within the spatial domain. The reversible data hiding scheme during this domain are often classified into 3 classes, i.e.

1) Data hiding by difference growth, 2) Data hiding by bar graph shifting, and 3) Data hiding by prediction error expansion.

In 2002, the primary distinction growth methodology was planned [1, 2]. In 2012, Ni et al. planned the primary bar graph shifting-based information concealment theme [3]. In 2007, Thodi and Rodriguez planned an information concealment theme supported prediction error growth [4].

Supported the above 3 schemes, several data hiding ways [57] are planned to reinforce hiding capacity or cut back the distortion of the stego-image. In the frequency domain, the cover image should be preprocessed by separate cosine transformation (DCT) [8], separate wavelet transformation (DWT) [9], or separate Fourier remodel (DFT) [10] to induce frequency coefficients. Once the frequency coefficients are changed slightly to embed the secret information, the stego image is often obtained by inversing the changed frequency coefficients. In 2001, Fridrich et al. proposed an invertible data hiding theme to change the quantization table by employing a second-order operate. In 2002, chang et al. embedded the secret data into the mid-frequency coefficients.

Next, Xuan et al utilized a reversible scheme to engraft information into the high-frequency DWT coefficients with bar graph modification.

http://www.ijettjournal.org

Page 27

International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014 In 2007, Chang Jiang et al.presented a lossless embedding theme for JPEG pictures. In the compression domain, the secret data are embedded by the alteration of the compression code. Through the compression methodology, the scale of the digital image information is often reduced considerably. Actually, we have a tendency to transmit digital image data within the compression format in our standard of living. Many researchers have interest in hiding data within the compression domain. Among compression Techniques, like JPEG, JPEG2000, VQ, and block truncation coding (BTC), VQ is a simple and efficient methodology that's wide used. Chang Jiang et al. proposed a reversible, data hiding algorithmic program based on the SMVQ. Within the same year, Yang et al. planned AN MFCVQ based, reversible watermarking theme by using four adjacent blocks to code the present block. However, the visual quality and hiding capability of yang et al.’s scheme weren't sensible enough. In 2009, Chang Jiang et al. used the conception of joint neighboring coding (JNC) within the VQ index table for embedding secrets with changeability. During this paper, a completely unique information hiding scheme based on the VQ codebook is explored. The proposed method uses a codebook that has been resorted by PCA (principle component analysis) and exploits the gap of two codeword’s, which are just like one image block, to embed the secret information. In keeping with the key to be embedded and also the difference between those 2 codeword’s, the initial image block is reworked into a difference variety table that's compressed by entropy coding before causing to the receiver. At the receiver finish, once cryptography the compressed code, the key information are often extracted, and also the image are often recovered as a VQ compressed image.

III. PROPOSED METHODOLOGY The proposed scheme uses AES encoding algorithmic program that uses an equivalent keys for each encoding and decryption. AES is AN iterated block cipher with a set block size of 128 and a variable key length. AES uses variable variety of rounds that are fastened. The key growth algorithmic program is based on the assumption of a 128 bit key. AES calls for a bigger variety of rounds once we use a key length aside from 128 bits. The key expansion algorithmic program should obviously generate an extended schedule for the 12 rounds needed by a 192 bit key and also the fourteen rounds needed by a 256 bit keys. If a change in one bit of the encoding key happens it'll have an effect on the spherical key for many rounds. The key expansion algorithm ensures that AES has no weak keys throughout every round; following operations are performed on every state 1.

2.

3.

Sub Bytes: each byte within the state is replaced by another one, using the S-Box. Shift Row: each row within the 4x4 array is shifted a particular quantity to the left.

Mix Column: a linear transformation on the columns of the state.

ISSN: 2231-5381

4.

Add round Key: each byte of the state is combined with a byte key.

3.1 THE SUBSTITUTE BYTES STEP This is a computer memory unit-by-byte substitution and also the substitution byte for every input byte is found by using the lookup table. The scale of the lookup table is 16 × 16. To seek out the substitute byte for a given input byte, we have a tendency to divide the input byte into 2 4-bit patterns, every yielding A whole number price between 0 and 15. We are able to represent these whole number values by their hex values zero through F. is one amongst the hex values employed as a row index and also the alternative as a column index for reaching into the 16×16 lookup table. The entries within the lookup table are constructed by a mix of GF (28) arithmetic and bit mangling. The goal of the substitution step is to reduce the correlation between input bits and output bits at the byte level. The bit mangling a part of the substitution step ensures that the substitution can't be described within the variety of evaluating a simple mathematical function. We have a tendency to initial fill every cell of the sixteen × sixteen table with the byte obtained by joining along its row index and also the column index. we next replace the worth in every cell by its multiplicative inverse in GF (28) supported the irreducible polynomial x8+x4+x3+x+1. The value 00 is replaced by itself since this component has no inverse. Let’s represent a byte stored in each cell of the table by b7b6b5b4b3b2b1b0 wherever b7 is that the msb and b0 the LSB. Therefore, the bit pattern stored 9 cells with row index nine and column index 9 is 10001010, showing that b7 is 1 and b0 is 0.

This byte-by-byte substitution step is reversed throughout decryption. The 16×16 lookup table for decryption is constructed by beginning get into an equivalent manner as for the encryption lookup table.

3.2 THE SHIFT ROW STEP The Shift Row transformation consists of 1.

2.

3.

4.

Not shifting the primary row of the state array at any condition.

Circularly shifting the second row by one byte to the left side.

Circularly shifting the third row by two bytes to the left side.

Circularly shifting the last row by three bytes to the left facet.

The input block is written in column-wise manner. That’s the primary four bytes of the input block fill the primary column of the state array and also the next four bytes the second column then on. For secret writing, the encoding steps are shifted in only the other fashion. At the start the primary row is left unchanged. The second row is shifted to right by one byte and also the third row to right by 2 bytes and also the last

http://www.ijettjournal.org

Page 28

International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014 row to right by 3 bytes. All shifts performed are circular manner.

3.3 MIX COLUMN STEP This step replaces every byte of a column by a function of all the bytes within the same column. additional exactly, every byte in an exceedingly column is replaced by twice that byte, and three times successive byte, and the byte that comes next, and the byte that follows. The words ‘next’ and ‘follow’ discuss with bytes within the same column, and there that means is circular, within the sense that the byte that's next to the one within the last row is that the one within the initial row. This stage called round Column is largely a substitution however it makes use of arithmetic of GF (28). Every column is operated individually. Every byte of every column is mapped into a brand new value that's a function of all four bytes within the column.

3.4 ADD ROUND KEY TRANSFORMATION This stage called AddRoundKey uses the 128 bits of state and is bitwise XORed with the 128 bits of the round key.

This operation is performed in column wise manner. This transformation is as easy as possible which helps in efficiency but it affects every bit of state.

3.5 IMAGE ENCRYPTION Assume an original image is within uncompressed format and every pixel with gray value falling directly into [0, 255] is presented by 8 bits.

Ba,b,c= ba,b,cΦ ra,b,c where ra,b,c are determined by an encryption key by using a standard stream cipher. Then, Ba,b,c are concatenated orderly since the encrypted data. Various of secure stream cipher methods might be used here to make sure which anyone without the encryption key, say for example a potential attacker or even the data hider, cannot acquire any information regarding unique content through the encrypted data.

3.6 DATA EMBEDDING Within the data embedding phase, some parameters are embedded right into a small number attached with encrypted pixels, and furthermore the particular LSB with the other encrypted pixels are compressed to generate a space for accommodating a further data along with the original data at the positions occupied through the parameters. The detailed procedure can be as follows In accordance with a data-hiding key, the data-hider pseudo-randomly selects Np encrypted pixels that may be utilized to hold the parameters for data hiding.

ISSN: 2231-5381

Here, Np is really a small positive integer, for instance, Np=20. The other (N-Np) encrypted pixels are pseudorandomly permuted and divided into a variety of groups, each and every of which contains L pixels.

The permutation way is usually dependant on the data-hiding key.

For every pixel-group, gather the M the very least considerable items of the L pixels, as well as denote them as B (k,1) , B (k,2) …… B(k,M*L) in which k can be a group index within [1,(N-Np)/L] and M is generally a positive integer less than 5. The data-hider also generates a matrix G sized (M*L – S) * M*L, that is consists of two parts.

The left part will be the identity matrix as well equally the suitable part is pseudo-random binary matrix produced from the data-hiding key.

For each and every group , which can be product with all the G matrix to create a matrix of size (M * L-S). That includes a sparse bits involving size S, when the information is embedded as well as organize the pixels in to the original form and repermutated to create a original image.

3.7 DATA EXTRACTION When the particular receiver has both data-hiding, he might make an effort to extract the embedded data Based on the data-hiding key, the values of M,L and S, the original LSB from the Np chosen encrypted pixels, as well as the (N-Np) * S/L - Np further bits might be extracted in the encrypted image containing embedded data. By putting the particular Np LSB within their original positions, the encrypted data with the Np determined pixels are retrieved, and their particular original gray values might be correctly decrypted while using the encryption keys. Within the following, we are going to recover the initial gray values with the other (N-Np) pixels.

This specific paper proposes a new novel scheme for separable reversible data hiding in encrypted image. Within the proposed scheme, the initial image is encrypted having an encryption key as well as the additional data are embedded in the encrypted image by using a data-hiding key. Through an encrypted image containing additional data, in the result the receiver only has the data-hiding key, he is able to acquire the extra data though he doesn't are aware of the image content. In case he's got just the encryption key, he is able to decrypt the received data to have an image exactly like the original one, but cannot extract the embedded additional data. In the event the receiver has both the data-hiding key and also the encryption key, they can extract the additional data and recover the initial image without the error if the amount of additional data will be not too big.

http://www.ijettjournal.org

Page 29

International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014 IV. CONCLUSION In this particular paper, a new scheme intended for separable reversible data hiding in encrypted image is proposed, which often includes image encryption, data embedding as well as data-extraction/image recovery phases. Within the first phase, this content owner encrypts the initial uncompressed image having an encryption key. Although a data-hider will not really know the dimensions as well as original written content, they may compress the smallest amount involving significant bits of the encrypted image employing a data-hiding step to make a new sparse space to accommodate the additional data.

By having an encrypted image containing additional data, the receiver may extract a further data only making use of the data-hiding key, or get the image just like the original one only using the encryption key. Once the receiver has each of the keys, they can extract the additional data and recover the original content without any error by exploiting the spatial connection in normal image within the event the quantity of more data is not too big. When the lossless compression technique is useful for the encrypted image containing embedded data, the additional data may be still extracted as well as the original content can as well be recovered considering that the lossless data compression will not affect the content with the encrypted image containing embedded data. However, the lossy compression method in suitable for encrypted images produced by pixel replacement just isn't suitable here considering that the encryption is performed by bit-XOR operation. Later on, a comprehensive combined image encryption and data hiding suitable for lossy compression should get further study

REFERENCES [1]. G.Braudway, K. Magerlin. And F. Mintezer. "protecting publicity available images with a visual image watermark," Proc. SPIE: optical security and Counterfeit Deterrence Techniques, Vol. 2659. pp.126-133, 1996.

[2]. B.Macq and J.Quisquater. "Cryptology for Digital TV broadcasting," Proc. Of IEEE. Vol. 83. No.6, pp 944-957, June 1995.

[3]. W. Zeng, “Digital watermarking and data hiding: technologies and applications,” in Proc. Int. Conf. Inf. Syst., Anal. Synth., vol. 3, pp. 223–229, , 1998.

[4]. N. Zhichenge, ,Y. Q. Shi,N. Ansari, and W. Su,“ Reversible Data Hiding” IEEE Transactions on circuits and systems for video technology, vol.16, No. 3, March 2006.

[5]. J. Cox, J. Kilian, T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans.

Image Process., vol. 6, no. 12, pp. 1673–1687, Dec. 1997.

ISSN: 2231-5381

[6]. Z. Tirkel, C. F. Osborne, and R. G. Van Schyndel, “Image watermarking a spread spectrum application,” in Proc. IEEE 4th Int. Symp. Spread Spectrum Techn. Applicat., vol. 2, pp.

785– 789, Sep. 1996.

[7]. A. van Leest, M. van der Veen, and F. Bruekers, “Reversible Image Watermarking,” in Proc.

Int. Conf. Image Processing, Vol. 2, pp. 731−734, 2003.

[8]. J. Huang and Y. Q. Shi, “An adaptive image watermarking scheme based on visual masking,” Electron. Lett., vol. 34, no. 8, pp. 748–750, 1998.

[9] I. S. Lee and W. H. Tsai, A new approach to covert communication via PDF Files, Signal Process. 90 (2) (2009) 557-565.

[10] T. Y. Liu and W. H. Tsai, A new steganographic method for data hiding in Microsoft Word documents by a change tracking technique, IEEE Transactions on Information Forensics and Security 2 (1) (2007) 24-30, 2007.

[12] W. Bender, D. Gruhl, N. Morimoto and A. Lu, Techniques for data hiding, IBM Systems Journal 35 (3-4) (1996) 313-336.

[13] J. Mielikainen, LSB matching revisited, IEEE Signal Processing Letters 13 (5) (2006) 285-287.

[14] C. H. Yang, C. Y. Weng, S. Wang and H. M. Sun, Adaptive data hiding in edge areas of images with spatial LSB domain systems, IEEE Transactions on Information Forensics and Security 3 (3) (2008) 488-497.

[15] Y. N. Wang and A. Pearmain, Blind image data hiding based on self reference,Pattern Recognition Letters 25 (15) (2004) 1681-1689.

[16]. C. W. Honsinger, P. Jones, M. Rabbani, and J. C. Stoffel, “Lossless Recovery of an Original Image Containing Embedded Data,” U.S. Patent 6 278 791 B1, Aug. 21, 2001.

[17] S. H. Wang and Y. P. Lin, Wavelet tree quantization for copyright protection watermarking, IEEE Trans. Image Processing, 13 (2) (2004) 154-165.

[18] C. M. Pun, A novel DFT-based digital watermarking system for images, Proceedings of 8th Int. Conf. on Signal Processing, Guilin, Yunnan, China, 2006, pp. 1245-1248.

[19] S. Pereira and T. Pun, Robust template matching for affine resistant image watermarks, IEEE Trans. on Image Process. 9 (6) (2000) 1123-1129.

[20] L. S. T. Chen, S. J. Lin and J. C. Lin, Reversible JPEGbased hiding method with high hiding-ratio, Int. Journal of Pattern Recog. and Artificial Intelligence, 24 (2010) 1-23.

[21] J. H. Lee and M. Y. Wu, Reversible Data-hiding method for palette-based images, Optical Engineering, 47 (2008) 047008-1-047008-9.

http://www.ijettjournal.org

Page 30