International Journal of Computer Engineering and Applications, Volume XI, Issue IX, September 17, ISSN

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1 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW Arbind Tiwary 1, A K Gupta 2 and Rajesh Kumar Tiwari 3 1 Department of MCA, Vinoba Bhave - University, Hazaribag, Jharkhand, India 2 Associate Professor, Dept. of Physics, Vinoba Bhave University, Hazatibagh 3 Professor & HOD CSE, R. V. S. Collecge of Engineering and Technology, ABSTRACT The Data hiding techniques have taken important role with the rapid growth of intensive transfer of multimedia content and secret communication. The Steganography is one of the methods used for the hidden exchange of information and it can be defined as the study of invisible communication that usually deals with the ways of hiding the existence of the communicated message. For hiding secret information in images, there exist a large variety of steganographic techniques. This paper intends to give an overview of image Steganography, its uses and techniques. It also attempts to identify the requirements of a good Steganography algorithm and briefly reflects on which Steganography techniques are more suitable for which applications. Keywords Cryptography, Steganography, LSB,, Encryption DecryptionIimage fie,overview,taxonomy [1] INTRODUCTION To understand steganography, we must first understand its predecessor: cryptography. Cryptography [1] - [4] is the art of protecting information by transforming it into an Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 1

2 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW unreadable format, called cipher text. To decipher this unreadable format, a secret key is required. Cryptography has followed man through many stages of evolution. Cryptography can be found as far back as 1900 B.C. in ancient Egyptian scribe using non-standard hieroglyphics in an inscription. From B.C. Hebrew scribes used ATBASH, a reversed alphabet simple solution cipher. From B.C. Julius Caesar used a simple substitution with the normal alphabet in government communications. Cryptography continued through history with many variations. Today cryptography has reached a new level, quantum cryptography. Quantum cryptography combines physics and cryptography to produce a new cryptosystem that cannot be defeated without the sender and receiver having the knowledge of the attempted and failed intrusion. Through the long history of cryptography, steganography was developed and flourished on its own. Steganography comes from the Greek stegano (covered or secret) and -graphy (writing or drawing). Steganography can be defined as the hiding of information by embedding messages within other, seemingly harmless messages, graphics or sounds. The first steganographic technique was developed in ancient Greece around 440 B.C. The Greek ruler Histaeus employed an early version of steganography which involved: shaving the head of a slave, tattooing the message Fig: 1 Shaved Head on the slaves scalp, waiting for the growth of hair to disclose the secret message, and sending the slave on his way to deliver the message. The recipient would have the slave s head to uncover the message. The recipient would reply in the same form of steganography. In the same time period, another early form of steganography was employed. This method involved Demerstus, who wrote a message to the Spartans warning of eminent invasions from Xerxes. The message was carved on the wood of wax tablet, and then covered with a fresh layer of wax. This seemingly blank tablet was delivered with its hidden message [3] successfully. Fig: 2 Wax Tablet Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 2

3 Steganography continued development in the early 1600s as Sir Francis Bacon used a variation in type face to carry each bit of the encoding. Steganography continued over time to develop into new levels. During times of war steganography is used extensively. During the American Revolutionary War both the British and American forces used various forms of Invisible Inks. Invisible Ink involved common sources, this Fig: 3 Invisible Ink included milk, vinegar, fruit juice, and urine, for the hidden text. To decipher these hidden messages required light or heat. During World War II the Germans introduced microdots [4]. Fig: 4 Microdots The microdots were complete documents, pictures, and plans reduced in size to the size of a period and attached to common paperwork. Null ciphers were also used to pass secret messages. Null ciphers are unencrypted messages with real messages embedded in the current text. Hidden messages were hard to interpret within the innocent messages. An example of an innocent message containing a null cipher [6], [7] is: Fishing freshwater bends and saltwater coasts rewards anyone feeling stressed. Resourceful anglers usually find masterful leapers fun and admit swordfish rank overwhelming any day. By taking the third letter in each word the following message emerges: Send Lawyers, Guns, and Money. [2] STEGNOGRAPHY MODEL Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 3

4 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW Relevant Terminologies: Fig: 5 Steganography Model a) Secret Message: The secret message is information which needs to be hidden into some suitable digital media. b) Cover Image: It is the carrier of message such as image, audio, video or other digital media. c) Stego Key: The key to entrench data in a cover which is again used to retrieve the data embedded is known as stego key. It may be a number generated by a pseudo-random number generator or can be a password for finding out the potential locations of embedding. d) Stego Image: The cover image with a secret message concealed within it is known as the Stego image. It is used at the recipient site for extracting the hidden message. e) Embedding Domain : The Embedding domain refers to the cover medium characteristics that are exploited in embedding message into it. It may be spatial domain when direct modification of the constituent elements of the cover is modified (e.g. pixels in an image) or it can be the frequency domain or transform domain if mathematical transformations are carried on the medium before embedding [15]. [3] IMAGE STEGNOGRAPHY As stated previously, images are considered as the most popular file formats used in steganography [1]-[5]. They are known for constituting a non-causal medium, due to the possibility to access any pixel of the image at random. In addition, the hidden information could remain invisible to the eye. However, the image steganography techniques will exploit "holes" in the Human Visual System (HVS). Finally, complete content and organizational editing before formatting. Please take note of the following items when proofreading spelling and grammar: B. Image files An image is defined as an arrangement of numbers and such numbers usually stand for different light intensities in different parts of the image. The numeric description takes the form of a lattice where the individual points given the name 'pixels'. Pixels are displayed horizontally, row by row. In a color scheme, the number of bits is known as the bit depth and this basically refers to the number of bits assigned to each pixel. Moreover, the smallest bit depth in the color scheme is 8, i.e., 8 bits are utilized to represent the color of each pixel. Both Monochrome and gray scale images usually utilize 8 bits for each pixel and such bits are capable of displaying up to 256 different colors or shades of gray. One more point to add is that Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 4

5 digital color images are known for being saved in 24-bit files and for utilizing the RGB color model. Almost all the color variations for the pixels of a 24-bit image are derived from three basic color terms: red, green, and blue, and each of these colors is represented by 8 bits. Thus, in any given pixel, the number of different shades of red, green, and blue can reach 256 that adding up to more than 16 million combinations that finally result in more than 16 million colors. The most prominent image formats, exclusively on the internet, are the graphics interchange format (GIF), joint photographic experts group (JPEG) format, and to a lesser degree, the portable network graphics (PNG) format [8]. The important issue to touch here is that most of the steganographic techniques attempt to exploit the structure of these formats. However, some literary contributions use the bitmap format (BMP) simply because of its simple and uncomplicated data structure. C. General Concepts Lossless compression is known for being preferable when the original data should stay in its entirety. In this manner, the original image information will never be removed, and this makes it possible the reconstruction of the original data from the compressed data. This is typical of images in GIF and BMP. Lossy compression saves storage space by discarding the points the human eyes find difficult to identify. In this case the resulting image is expected to be something similar to the original image, but not the same as the original. JPEG compression uses this technique. A cover image is the image designated to carry the embedded bits or secret A stego image refers to the image carrying the hidden message. A stego key is secret information necessary to get the hidden message from the stego image. [4] TAXONOMY OF STEGANOGRAPHY TECHNIQUE There are quite a lot of approaches in classifying steganographic techniques but these approaches can be classified in accordance with the type of covers used with secret communications. Another possibility is done via sorting such approaches depending on the type of cover modification already applied in the process of embedding. The second approach is adopted in this work, although in some cases an exact classification is not possible. In general, the process of embedding can be defined as follows: Let C denote the cover carrier and C in the stego image. Let R represent the optional (as a seed used to encrypt the message or to generate a pseudo-random noise, which can be set to {φ} for simplicity), and let M be the message to be sent. Then, Em represents an embedded message and Ex represents the extracted message. Therefore, Em : C R M C (1) Ex ( Em(c,r,m)) m, c C, r R,m M (2) To distinguish between different steganographic techniques in a wide sense, one must take into consideration both the methods that modify the image and those that modify the image file format. Though lossy compression methods result in smaller image file sizes, they increase the possibility of the partial loss of an embedded message because surplus image data is to be eliminated in these techniques. Lossless compression does not compress the image file as Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 5

6 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW much. As a result, researchers have come up with different steganographic algorithms that suit such compression types. Steganographic techniques that modify image files for hiding information include the following: Least significant bit substitution technique(lsb) Spatial domain; Transform domain; Spread spectrum; Statistical methods; and Distortion techniques. Steganographic techniques that modify the image file format involve file embedding and palette embedding. In addition, there are techniques that modify the elements in the visual image including: The image generation technique and the image element modification technique. Finally, there is a special type of the spatial and transform domain techniques called the adaptive steganography technique, which we also describe for completeness. D. Least significant bit substitution technique(lsb) In LSB steganography, the least significant bits of the cover media s digital data are used to conceal the message. The simplest of the LSB [16] steganography techniques is LSB replacement. LSB replacement steganography flips the last bit of each of the data values to reflect the message that needs to be hidden. Consider an 8-bit gray scale bitmap image where each pixel is stored as a byte representing a gray scale value. Suppose the first eight pixels of the original image have the following gray scale values: To hide the letter B whose binary value is , we would replace the LSBs of these pixels to have the following new gray scale values: Note that, on average, only half the LSBs need to change. The difference between the cover (i.e. original) image and the stego image will be hardly noticeable to the human eye. However, one of its major limitations is small size of data which can be embedded in such type of Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 6

7 images using only LSB. LSB is extremely vulnerable to attacks. LSB techniques implemented to 24 bit formats are difficult to detect contrary to 8 bit format. Another example of LSB technique is: Consider a grid for 3 pixels of a 24-bit image and the number 300 is to be embedded using LSB technique. The resulting grid is as follows: PIXELS: ( ) ( ) ( ) B: ( ) ( ) ( ) Here the number C was embedded into the first 8 bytes of the grid, only the 2 bits needed to be changed according to the embedded message.on average, only half of the bits in an image will need to be modified to hide a secret message using the maximum cover size. E. Spatial domain These techniques are based on gray level mappings, where the type of mapping used depends on the criterion chosen for enhancement [9], [10]. As an example, consider the problem of enhancing the contrast of an image. Let r and s denote any gray level in the original and enhanced image respectively. Suppose that for every pixel with level r in original image. We create a pixel in the enhanced image with level S=T( r ). If T(r) has the form as shown: Fig: 6 Spatial Domain The effect of this transformation will be to produce an image of higher contrast than the original by darkening the levels below a value m and brightening the levels above m in the original pixel spectrum. The technique is referred to as contrast stretching. The values of r below m are compressed by the transformation function into a narrow range of S towards the dark end of the spectrum; the opposite effect takes place for values of r above m. In the limiting case shown in figure, T(r) produces a 2-level (binary) image. This is also referred to as image thresholding. Many powerful enhancement processing techniques can be formulated in the spatial domain [of an image. Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 7

8 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW F. Transform Domain Techniques Transform domain embedding can be defined as a domain of embedding techniques for which a number of algorithms have been suggested. The process of embedding data in the frequency domain of a signal is much stronger than embedding principles that operate in the time domain. Transform domain techniques have an advantage over LSB techniques because they hide information in areas of the image that are less exposed to compression, cropping, and image processing. Some transform domain [11], [12] techniques do not seem dependent on the image format and they may out run lossless and lossy format conversions. G. Spread Spectrum Technique Spread spectrum transmission [13],[14] in radio communications transmits messages below the noise level for any given frequency. When employed with steganography, spread spectrum either deals with the cover image as noise or tries to add pseudo-noise to the cover image. H. Statistical Methods Also known as model-based techniques, these techniques tend to modulate or modify the statistical properties of an image in addition to preserving them in the embedding process. Statistical steganographic techniques exploit the existence of a 1-bit, where nearly a bit of data is embedded in a digital carrier. This process is done by simply modifying the cover image to make a sort of significant change in the statistical characteristics if a 1 is transmitted, otherwise it is left unchanged. To send multiple bits, an image is broken into subimages, each corresponding to a single bit of the message. However, statistical steganographic methods in their simplest form, for which sub-images are simply sub-rectangles of the original image, are vulnerable to cropping, rotating, and scaling attacks, along with any attacks that work against the watermarking technique. To counter these attacks, the sub-images could be selected based on picture elements, for example, the faces in a crowd, and error correction coding could be utilized within the message. These defenses can make the statistical steganographic method approximately as robust as the underlying watermarking scheme I. Distortion Technique Distortion techniques require knowledge of the original cover image during the decoding process where the decoder functions to check for differences between the original cover image and the distorted cover image in order to restore the secret message. The encoder, on the other hand, adds a sequence of changes to the cover image [17], [18]. So, information is described as being stored by signal distortion. Using this technique, a stego-object is created by applying a sequence of modifications to the cover image. This sequence of modifications is selected to match the secret message required to transmit. The message is encoded at pseudo-randomly chosen pixels. If the stego-image is different from the cover image at the given message pixel, then the message bit is a 1. Otherwise, the message bit is a 0. The encoder can modify the 1 value pixels in such manner that the statistical properties of the image are not affected (which is different from many LSB methods). However, the need for sending the cover image limits the benefits of this technique. As in any steganographic technique, the cover image should never be used more than once. If an attacker tampers with the stego-image by cropping, Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 8

9 rotating, or scaling, the receiver can easily detect the modification. In some cases, if the message is encoded with error correcting information, the change can even be reversed and the original message can be fully recovered. An early approach to hiding information was to do so in text. Most text-based hiding techniques are of the distortion type. For example, the layout of a document or the arrangement of words might show or reflect the presence of information. Considering one of these techniques can show the adjustment of the positions of lines and words where spaces and invisible characters are added to the text, providing a method of sending hide information. J. File Embedding Different image file [19] formats are known for having different header file structures. In addition to the data values, such as pixels, palette, and DCT coefficients, secret information can also be hidden in either a header structure or at the end of the file. For example, the comment fields in the header of JPEG images usually contain data hidden by the invisible Secrets and Steganozorus. Camouflage, JpegX, PGE10, and PGE20 add data to the end of a JPEG image. Image storage formats such as TIFF, GIF, PNG, and WMF have a file header that can be exploited to hide arbitrary information. In this case, that arbitrary data may be a secret message. It is possible to append data to many image storage formats without affecting the image. When the image is processed for display, the image user will decode the image size from the file header, and any tracking information attached to the end of the file will be ignored. Using this technique, it is possible to attach a message of any size to a cover image. However, the message could be removed from the cover image by simply resaving the image in the same file format. The limitations of this method are that despite the large payload, it is not that difficult to identify and defeat, it is weak when lossy compression and image filtering are concerned, and the resaving of the image implies complete loss of hidden data. K. Pallet Embedding In a palette-based image, what matters is the fact that only a subset of colors from a particular color space is used to colorize the image. Researchers believe that every palette-based image format consists of two parts. The first part is a palette that assigns N colors as a list of indexed pairs,(i, c i ) assigning a color vector c i to every index i, and the actual image data, which specifies a palette index for each pixel, rather than the color value itself. The file size gets decreased via this approach when only a limited number of color values are used in the image. Two of the most popular formats are the graphics interchange format (GIF) and the bitmap format (BMP). However, owing to the availability of advanced compression techniques, their use has diminished in some cases, the palette itself can be used to hide secret information. Because the order of the colors in the palette usually does not matter, the ordering of colors can be used to transfer information. In essence, a hidden message can be embedded using the difference between two colors in the palette (i.e., one secret message bit for every two colors in the palette). Color palettes are used to minimize the amount of information images that are used to represent colors. Since steganographic message within the bits of the palette and/or the indices is embedded in the palette-based steganography, one must be careful not to exceed the maximum number of colors. Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 9

10 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW [5] PERFORMANCE MEASURE As a performance measure [20] for image distortion due to embedding, the well-known peaksignal to noise ratio (PSNR), which is categorized under difference distortion metrics, can be applied to stego images. It is defined as: PSNR=10* log (255 2 /MSE) (3) n 1 y=0 n 1 Where MSE= x=0. (f(x, y) g(x, y)) 2 /N 2 (4) Where f(x, y) and g(x, y) means the pixel value at the position (x, y) in the cover-image and the corresponding stego-image respectively. PSNR is often expressed on a logarithmic scale in decibels (Db). PSNR values below 30 Db indicate low quality (i.e., distortion caused by embedding is clear). A high-quality stego image should strive for a PSNR of 40 Db, or higher. [6] EVOLUATION OF DIFFERENT TECHNIQUE All the above mentioned algorithms with respect to image steganography are not void of weak and strong points. Consequently, it is important to decide the most suitable approach to be applied. As defined before, there are several parameters to measure the performance of the steganographic system [21]. LSB technique in the spatial domain is a practical way to conceal information but, at the same time, it is vulnerable to small changes resulting from image processing or lossy compression. The promising techniques such as DCT, DWT and the adaptive steganography are not tended to attacks, especially when the hidden message is small. This can be justified in relation to the way they change the coefficients in the transform domain, thus, image - distortion is kept to a minimum. Spread spectrum techniques are generally quite robust against statistical attacks, since the hidden message is spread throughout the image. However, a determined attacker is capable of compromising the embedded data using some digital processing, such as noise reduction filters, which are similar to the ones used in the decoding process to estimate the original cover. Spread spectrum encoding is extensively used in military communications due to its robustness against detection. The statistical techniques in most cases are vulnerable to cropping, rotating, and scaling attacks, along with any attacks that work against the watermarking technique. Defenses could be considered to make the statistical techniques as robust as the watermarking scheme. The payload capacity and invisibility depends on the cover image selected. Unlike many LSB methods, distortion techniques do not upset any statistical properties of the image. In contrast, the need to send the cover image over a secure channel limits the worth of this technique. Techniques that modify image file formatting information have the following drawbacks: they have a large payload; however, they are easily detected and defeated; they are not robust against lossy compression and image filters, and the issue of saving the image one more time totally breaks the hidden data. Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 10

11 Hiding information via steganographic techniques that modify the elements in the visual image results in a stego-image that will survive rotation, scaling and much lossy compression like JPEG. A reasonable payload capacity can be achieved with this technique as well. Table 1 summarizes the evaluation of the mentioned techniques through this paper. Imperceptibility Robustness Payload Capacity LSB High* Low High Transform Domain High High Low Spread Spectrum High Medium High Statistical Techniques Medium* Low Low* Distortion Techniques Low Low Low File and Pallet Embedding High* Low Low TABLE 1: A comparison of Image Steganography Techniques *: Indicates dependency on the used cover image [7] CONCLUSION In this paper we have presented an overview of different image stegnographic techniques for both lossy and lossless image format such as JPEG & BMP. It can be concluded here that the consequences are presented in terms of a taxonomy that focuses on three principles of steganographic techniques for hiding information in image files. Those techniques include modifying the image in the spatial domain. Those in the transform domain, and those modifying in the image file formatting. Each of these techniques tries to satisfy the three most important factors of steganographic design (imperceptibility or un-detectability, capacity, and robustness). From TABLE: 1, one can deduce that while one technique may lack in payload capacity, another may lack in robustness. For example, file formatting techniques we can store large amounts of information, but they are easily detected and attacked. Likewise, LSB techniques in a spatial domain have a high payload capacity, but they often fail to prevent statistical attacks and are thus easily detected. It is important to notice that the hiding capacity in LSB technique depends on the cover image being used. LSB in BMP images are capable of hiding relatively a large message, but large amount of altered bits results in a larger possibility of detection by human eye. While LSB in GIF images is approximately the same as that of using LSB in BMP images. The only difference is related to the structure of the GIF images, since they only have a bit depth of 8. Thus, the amount of hidden information is less than with BMP. In addition, LSB in GIF is mainly dependent on the file format and the image itself. Incorrect choice of cover image could result in visible message. Besides, file and spatial domain approaches are considered not to be robust against lossy compression and filtering. Transform domain techniques are considered more robust for lossy compression image Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 11

12 DIFFERENT IMAGE STEGANOGRAPHY TECHNIQUES: AN OVERVIEW formats, but this advantage is achieved at the expense of payload capacity. However, it is possible to defeat the transform domain techniques, but with some efforts. For most of steganography applications, JPEG file format can be used, especially for images that have to be communicated over an open systems environment like the Internet. Thus, for an agent to send secret information using steganographic techniques, he/she must select a suitable steganographic algorithm and suitable cover image as well. The required application is the only thing to decide the most appropriate steganographic method among all the present image steganographic techniques. In short, one must have the determination to compromise on some characteristics to ensure the high performance of other characteristics. [8] ACKNOWLEDGEMENT The author s wants to heartily thank their supervisor, Dr. A.K. Gupta, Associate Professor, Dept. of Physics, Vinoba Bhave University, Hazatibagh and Co-Supervisor Prof.(Dr.) Rajesh Kumar Tiwari, Professor & HOD CSE, R. V. S. Collecge of Engineering and Technology, Mango, Jamshedpur for their kind support.. REFERENCES [1] Gadadhar Sahoo, Rajesh Kumar Tiwari,"Some new methodologies for image hiding using steganographic techniques",international journal of Information Analysis and Processing,vo. 1,iss. 1,pp.25-31,2008 [2] Nagham Hamid,Abid Yahya,R. Badlishah Ahmad,Osamah M. Al-Qershi "Image Steganography Techniques: An erview", IJCSS, VOL.6, Issue.3, pp , 2012 [3] M. D. Swanson, B. Zhu, and A. H. Tewfik, Robust data hiding for images, in Proc. IEEE Digital Signal Processing Workshop, Loen, Norway, Sept. 1996, pp [4] Alaa A. Jabbar Altaay, Shahrin bin Sahib, and Mazdak Zamani, An Introduction to Image Steganography Techniques, International Conference on Advanced Computer Science Applications and Technologies,Kuala Lumpur, Malaysia, Nov. 2012, pp [5] Mehdi Kharrazi, Husrev T. Sencar Nasir Memon, Performance study of common image steganography and steganalysis techniques Journal of Electronic Imaging,vol.15,issue.4,pp. 1-16,Oct-Dec 2006Rr [6] A Nag, S Biswas, D Sarkar,PP Sarkar,"A novel technique for image steganography based on Block-DCT and Huffman Encoding" -International Journal of Computer Science and Information Technology, Volume 2, Number 3, June 2010,pp [7] N. F. Johnson and S. Katzenbeisser, "A survey of steganographic techniques.", in S. Katzenbeisser and F. Peticolas (Eds.): Information Hiding, pp Artech House, Norwood, MA, [8] R.Amirtharajan, R. Akila,P.Deepikachowdavarapu, A Comparative Analysis of Image Steganography International Journal of Computer Applications,Volume 2 No.3, May 2010, pp [9] Mr. Falesh M. Shelke, Miss. Ashwini A. Dongre,Mr. Pravin D. Soni, Comparison of different techniques for Steganography in images International Journal of Application or Innovation in Engineering & Management (IJAIEM),Volume 3, Issue 2, February 2014, pp [10] Johnson, N.F and Jajodia, S., Exploring Steganography:Seeing the Unseen, Computer Journal, February Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 12

13 [11] Rajarathnam ChandramouliMehdi KharraziNasir Memon, Image Steganography and Steganalysis: Concepts and Practice, International Workshop on Digital Watermarking,Volume 2939 of the book series(lncs),2004,pp [12] Chi-Kwong Chan, L.M. Cheng, Hiding data in images by simple LSB substitution, Pattern Recognition, Vol.37, pp , [13] D. C. Wu and W. H. Tsai, A steganographic method for images by pixel-value differencing, Pattern Recognition Letters, vol. 24, no. 9-10, pp , [14] N.Provos, P.Honeyman, Hide and seek: an introduction to steganography, IEEE Security and Privacy, 1(3)(2003),pp [15] A. Cheddad, J. Condell, K. Curran and P. Mc Kevitt, "Digital Image Steganography: Survey and Analyses of Current Methods, Signal Processing, Volume 90, Issue 3, pp , March [16] Nitin Jain, Sachin Meshram, Shikha Dubey, Image Steganography Using LSB and Edge Detection Technique, International Journal of Soft Computing and Engineering,Volume-2,Issue-3,pp ,July 2012 [17] Anil Kumar,Rohini Sharma, IA Secure Image Steganography Based on RSA Algorithm and Hash-LSB Technique, International Journal of Advanced Research in Computer Science and Software Engineering,Volume 3, Issue 7,pp ,July 2013 [18] Asad.M., Gilani, J., Khalid.A., An enhanced least significant bit modification technique for audio steganography, Computer Networks and Information Technology (ICCNIT), IEEE, Pages No , July, [19] Amanpreet Kaur,Renu Dhir and Geeta Sikka, A New Image Steganography Based On First Component Alteration Technique, International Journal of Computer Science and Information Security,Vol. 6, No. 3,pp 53-56,2009 [20] Mansi S. Subhedar,Vijay H. Mankar Current status and key issues in image steganography: A survey, Computer Science review,13-14,pp ,2014 [21] Image Stegnography, Arbind Tiwary is a Research Scholar in the Department of MCA, Vinoba Bhave - University, Hazaribag, Jharkhand, India. He Qualified Doctoral (Ph.D.) Eligibility Entrance Test 2014(DEET 2014) of Vinoba Bhave University, Hazaribag & top scorer in his subject.. He has completed Ph.D. course work from VBU, Hazaribag. His research interests are Steganography, Data Security Watermarking & cryptography etc. Arbimd Tiwary, A.K.Gupta and Rajesh Kumar Tiwari 13