DESIGNING EFFICIENT STEGANOGRAPHIC ALGORITHM FOR HIDING MESSAGE WITHIN THE GRAYSCALE COVER IMAGE

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1 DESIGNING EFFICIENT STEGANOGRAPHIC ALGORITHM FOR HIDING MESSAGE WITHIN THE GRAYSCALE COVER IMAGE 1 Ram Krishna Jha, 2 Ravi Kumar Mishra 1 Dept. of Information Technology, G L Bajaj Institute of Technology & Management, Greater Noida, India 2 Dept. of Information Technology, Birla Institute of Technology, Ranchi, India Abstract- Steganography is the art and science of communicating in such a way that the very existence of communication is not revealed to a third party, in order to communicate without being detected. Steganography sometimes is used when encryption is not permitted, or commonly, steganography is used to supplement encryption. An encrypted file may still hide information using steganography, so even if the encrypted file is deciphered, the hidden message is not seen. Steganography comes from the Greek words Steganos (Covered) and Graptos (Writing). Steganography usually refers to information or a file that has been concealed inside a digital Picture, Video or Audio file. The important issue of modern communication is establishing secret communication while using public channel and is achieved by steganography. We propose Coherent Steganographic Technique using Segmentation. The cover image and the secret file is divided into number of segments and then compare, whose segment value is near about the segment value of secret file, so that we can replace the values which is not visible by human eyes. Keywords- Stego-key, Standard-Deviation, Replacement, Steganography, Security, Hiding I. INTRODUCTION Security is the degree of protection against danger, damage, loss, and crime. Security as a form of protection are structures and processes that provide or improve security as a condition. Security has to be compared to related concepts: safety, continuity, reliability. The key difference between security and reliability is that security must take into account the actions of people attempting to cause destruction. Steganography or Stego as it is often referred to in the IT community, literally means, covered writing" which is derived from the Greek language. Steganography is defined by Markus Kahn [1] as follows, "Steganography is the art and science of communicating in a way which hides the existence of the communication. In contrast to Cryptography, where the enemy is allowed to detect, intercept and modify messages without being able to violate certain security premises guaranteed by a cryptosystem, the goal of Steganography is to hide messages inside other harmless messages in a way that does not allow any enemy to even detect that there is a second message present". In a digital world, Steganography and Cryptography are both intended to protect information from unwanted parties. Both Steganography and Cryptography are excellent means by which to accomplish this but neither technology alone is perfect and both can be broken. It is for this reason that most experts would suggest using both to add multiple layers of security. Steganography can be used in a large amount of data formats in the digital world of today. The most popular data formats used are.bmp,.doc,.gif,.jpeg,.mp3,.txt and.wav. Mainly because of their popularity on the Internet and the ease of use of the steganographic tools that use these data formats. These formats are also popular because of the relative ease by which redundant or noisy data can be removed from them and replaced with a hidden message. Steganographic technologies are a very important part of the future of Internet security and privacy on open systems such as the Internet. Steganographic research is primarily driven by the 184

2 lack of strength in the cryptographic systems on their own and the desire to have complete secrecy in an open-systems environment. Many governments have created laws that either limit the strength of cryptosystems or prohibit them completely. This has been done primarily for fear by law enforcement not to be able to gain intelligence by wiretaps, etc. This unfortunately leaves the majority of the Internet community either with relatively weak and a lot of the times breakable encryption algorithms or none at all. Civil liberties advocates fight this with the argument that these limitations are an assault on privacy. This is where Steganography comes in. Steganography can be used to hide important data inside another file so that only the parties intended to get the message even knows a secret message exists. To add multiple layers of security and to help subside the "crypto versus law" problems previously mentioned, it is a good practice to use Cryptography and Steganography together. As mentioned earlier, neither Cryptography nor Steganography are considered "turnkey solutions" to open systems privacy, but using both technologies together can provide a very acceptable amount of privacy for anyone connecting to and communicating over these systems. Internet communication has become an integral part of the infrastructure of today s world. The information communicated comes in numerous forms and is used in many applications. In a large number of these applications, it is desired that the communication be done in secrete. Encryption provides an obvious approach to information security, and encryption programs are readily available. However, encryption clearly marks a message as containing interesting information, and the encrypted message becomes subject to attack. Steganography presents another approach to information security. In steganography, data is hidden inside a vessel or container that looks like it contains only something else. A variety of vessels are possible, such as digital images, sound clips, and even executable files. II. RELATED WORKS Designing an Embedded Algorithm for Data Hiding using Steganographic Technique by File Hybridization is also a good method proposed by G. Sahoo and R. K. Tiwari in 2008[2]. Their proposed method works on more than one image using the concept of file hybridization. This particular method implements the cryptographic technique to embed two information files using steganography. And due to this reason they have used a stego key for the embedding process. Unfortunately, modifying the cover image changes its statistical properties, so eavesdroppers can detect the distortions in the resulting stego-image s statistical properties. In fact, the embedding of high-entropy data (often due to encryption) changes the histogram of colour frequencies in a predictable way. So, in order to obtain more security in prescribed method, we have embedded the secret information behind an image of 8 times the size of secret information file to hide any remarkable change in the final image and also it helps the secret information remain scattered throughout the carrier image which will make the changes in the histogram look like noise. A public key method of Steganography is proposed by Prof. Samir Kumar Bandyopadhyay and Sarthak Parui [3]. In modern Steganography, secret information can be embedded in any kind of multimedia file, viz. image, audio or video. In this thesis mostly use image file as the carrier prior to send the secret information via some media. Now if we modify the carrier image, its statistical properties get changed. Hence an opponent can detect the distortion from the statistical property of the resulting stego image. Embedding higher entropy data changes the histogram of the carrier image significantly. Thus, it is a common practice to embed data in the Least Significant Bits of the carrier image file. Jin-Suk Kang proposed steganography algorithm using block-based adaptive threshold [4]. Initially the bit-plane blocks of the cover image and the payload are compared and if the blocks are similar, then those blocks of the payload are embedded in the cover image. Here proposed a new method of the adaptive steganography using complexity on bit planes of color image. Applying fixing threshold and variable length, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we investigated the complexity on bit plane and data, similarity insert information into bit planes. As a result, the proposed method increased the insertion capacity and improved the image quality as compared to fixing threshold and variable length method. In this paper, the adjustment threshold has been calculated on color images using characteristics of bit-plane and multi-channels while applying this to propose steganography method. The existing BPCS method had applied permanent threshold regardless of the channel and bit-plane [5][6]. As the result, it is hard to find the optimum insertion threshold value depending on the amount of information to be inserted. Also, as a result of using same permanent threshold value for color channels, we could see the difference in degradation of image quality on color stego image in which the information is inserted. Therefore, the proposed research is to solve the problem of permanent insertion threshold value applied to color images, improve image quality and to increase the information inserting capacity. 185

3 Vijayalakshmi proposed modulo based image steganography algorithm[7]. The method combines samples of LSB bits using addition modulo to get the value which is compared to the part of the payload. If these two values are equal, no change is made in sample otherwise add the difference of these two values to the sample. This paper has proposed a modulo based LSB image steganography algorithm that can effectively resist image steganalysis based on histogram analysis and also statistical analysis. The proposed method combines samples of LSB bits by using addition modulo to form the value which is compared to the part of the secret message. If these two values are equal, no change is made. Otherwise, add the difference of these two values to the sample. Thus, this proposed method embeds the part of the secret message effectively. Statistical analysis is performed on stego image created using the steganography technique. In this work, a modulo based image steganography algorithm was proposed for both colour and black-nwhite images. The proposed algorithm was stimulated with secret data using Lena image as the cover image. The resultant stego image obtained after embedding of the secret message does not show any change when compared to original cover image. Histogram and statistical analysis were performed on the stego image and proved that the proposed method can effectively resist image steganalysis. Comparision of the statistical values like mean, variance and RMS for proposed method results with existing LSB steganography method was also done[8]. From these statistical analyses, it was also inferred that changes in values were obtained only in the fourth or fifth decimal places, thereby not affecting the appearance of the image. Thus, the proposed method provides greater security for the hidden data. Kang Leng Cheiew and Josef Pieprzyk proposed a scheme to estimate the length of hidden message through histogram quotient in Binary image embedded by using Boundary pixels Steganography technique[9]. In this paper, propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, and then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message. The proposed method in this paper manages to detect the steganography developed in. In addition, our method can also estimate the length of the embedded message. In the estimation, we first build the 512 patterns histogram from a binary image as the distinguishing statistic. From this 512 patterns histogram, we compute the histogram difference to capture the changes caused by the embedding operation. After that, matrix right division is performed to create histogram quotient. Finally based on the histogram quotient, the length of the embedded message is estimated. We have used significantly large image database which consists of 5931 binary images (1 set of cover images and 8 sets of stego images) to test the proposed method. From the experiment results obtained, we conclude that our proposed method has effectively estimated the hidden message length with low estimation error. III. PROPOSED ALGORITHM Our proposed algorithm is influence by Least Significant Bit (LSB) method which replaces the last bit in a 8 bit byte. Replacing LSB in each byte will not be noticeable to human eye or ear depending on the type of the file. As LSB method changes value of a byte and ineffect that changes the colour or sound therefore more noise in a file, the harder it will be for a human to notice any minute change. In this technique sequence of 8-bit secret data is encoded as fixed-length 12-bit codes. The code from value 0 to 255 represents one character sequences consisting of the corresponding 8-bit character. The drawback of this technique is that after injecting the secret message the carrier file become larger than the unmodified original file Encoding: 1. Select a Cover image 2. Breaking up the image into Blocks 3. Find the Standard Deviation of All the Blocks 4. Select the input Message 5. Find the ASCII value of each Characters 6. Find the Standard Deviation of All the Characters 186

4 1. Subtracting the Standard Deviation of each block from the Standard Deviation of ASCII value of All the Characters 2. Selecting the Block corresponding to minimum Difference 3. Select unique pixel value as X and find value of Y by using Random function 4. Continuing the above steps until each and every character of the given text has been exhausted 5. Finally we got the Encoded image 3.2. Decoding: 1. Divide the Encoded image into Blocks 2. Wwe know the Encoded block of Encoded image, put unique pixels value of Encoded block in an array 3. Put first element of array in another variable X and find corresponding value of Y Using Random function 4. Check if value of Y is greater than 256 then apply MOD(Y, 256). 5. Put encoded image s pixels value into string in respect to X and Y co-ordinate 6. Repeat steps 3 to 5 until all the value of (X, Y) Selecting an image: IV. RESULT Breaking image into 16 sub-images: Finding Standard Deviation of each block: Selecting text string (Input): BIRLAINSTITUTEOFTECHNOLOGY Finding Acii Value of each character: Finding Standard Deviation of String s Ascii Value: Starting from the beginning considering each character at a time. FOR EXAMPLE let the text be BIRLAINSTITUTEOFTECHNOLOGY and it s S.D will be Subtracting the S.D of each block from the Standard Deviation of ascii value.the minimum difference is which corresponds to the twelfth blocks where Standard Deviation Value is Selecting the block corresponding to the minimum difference. Select unique pixel value as X and find value of Y by using function (Y=X+13*X-9). Finding X, Y co-ordinates for replacing with Ascii Value of each character. X Y

5 Considering the first character B The ascii value of B is 66. The first X,Y co-ordinates for B is (14,187). Finally replacing at the point of X, Y co-ordinates (14,187) by the ascii value of B. Continuing the above steps until each and every character of the given text has been exhausted. Finally we got the Encoded image. Decoding: B I R L A I N S T I T U T E O F T E C H N O L O G Y V. CONCLUSION Steganography can be used for a variety of reasons. Legitimate purposes include watermarking images for copyright protection. Digital watermarks are similar to Steganography in that they appear to be part of the original object and are not easily detectable by the casual eye. Steganography can also be used to tag notes to online images and is used to maintain the confidentiality of valuable information. All the methods used in this report for embedding data in an image work on the principle of one image file. A new technique can be designed based on the concept that a single image file maybe divided into two or more sub image files and based on our requirements. We can embed the required data into a particular chosen sub image file which is a part of mother image file. This concept helps us in designing a methodology for both hiding and extracting information. Our technique is less prone to attacks and since the data is strongly encrypted and the cost of retrieving it by unauthorized persons is extremely high. Since the pixels are replaced with almost identical pixels, it is difficult to even identify that there is a second message hidden. So, we hope that our technique will be used widely in the future. 188

6 REFERENCES [1] Symmetric key cryptography using random key generator, A.Nath, S.Ghosh,.A. Mallik, Proceedings of International conference on SAM-2010 held at Las Vegas(USA) July,2010, Vol-2,P [2] Dr. G. Sahoo, R. K. Tiwari, Designing an Embedded Algorithm for Data Hiding using Steganographic Technique by File Hybridization, January [3] S.K.Bandyopadhyay, Debnath Bhattacharyya, Poulumi Das, S. Mukherjee, D. Ganguly, A Tutorial Review on steganography, August [4] Jin-Suk Kang, Yonghee You and Mee Young Sung (2007): Steganography using Block- Based Adaptive Threshold, International symposium on Computer and Information. [5] D. C. Wu and W. H. Tasi, A Steganographic Method for Image by Pixel-Value Differencing, Proc. of Pattern Recognition Letters, Vol.24, pp , [6] M. Niimi, H. Noda, and E. Kawaguchi, Steganography Based on Region Segmentation with a Complexity Measure, Proc. of the Systems and Computers in Japan, Vol.30, No.3, pp , [7] Dr. V. Vijayalakshmi, Dr. G. Zayaraz, and V. Nagaraj A Modulo Based LSB Steganography Method, International Conference on Control, Automation, Communication and Energy Conservation [8] J. Fridrich, M. Goljan, and R. Du, Detecting LSB Steganography in Color and Gray-Scale Images, Magazine of IEEE Multimedia Special Issue on Security, pp , Nov [9] Kang Leng Chiew, Josef Pieprzyk Estimating Hidden Message Length in Binary Image Embedded by Using Boundary Pixels Steganography

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