Hiding And Encrypting Binary Images Using A Different Approach

Hiding And Encrypting Binary Images Using A Different Approach Dr. P V Ramaraju 1, G.Nagaraju 2, M.Veeramanikanta 3, V.Sree Lekha 4, Mubashirunnisa 5, Y.Manojkumar 6 1 Professor, 2 Asst.Professor, 3,4,5,6 B.Tech Students, 1, 2, 3,4,5,6 Department of ECE, SRKR Engineering College, Bhimavaram, India. Abstract: Information security is one of the main issues in communication to ensure that unauthorized user can t get unintended information. Cryptography and Steganography are such techniques to provide information security. In this paper a new technique proposes a Steganography using pixel indicator method and a model is proposed for data embedding by using various patterns to increase the complexity. In this approach, the basic idea is to replace the Least Significant Bits of the cover image with the bits of the messages to be hidden without destroying the property of the cover image significantly. The LSB-based technique is the simple one and it is difficult to differentiate between the cover-object and stego-object if few LSB bits of the cover object are replaced. The cover image containing hidden image is performed encryption with the secret key image. By using the secret key image, the chance of getting attacked by the attacker is reduced. Decrypting the encrypted image and retrieving the hidden images can be done in reverse process. Keywords Steganography, Image Encryption, Image Decryption, Image Hiding, Secret Key Image. I. INTRODUCTION The growing use of Internet need to store, send and receive personal information in a secured manner. For this, we may adopt an approach that can transfer the data into different forms so that their resultant data can be understood if it can be returned back into its original form. This technique is known as encryption. However, a major disadvantage of this method is that the existence of data is not hidden. If someone gives enough time then the unreadable encrypted data may be converted into its original form. A solution to this problem has already been achieved by using a technique named with the Greek word steganography by which we mean writing in hiding. Steganography is derived from the Greek word steganographic which means covered writing. Steganography is a data hiding technique that hides image, audio and video in image content. Steganography is advantageous than cryptography which is another data hiding technique that in steganography data hiding is invisible and undetectable. The main purpose of steganography is to hide data in a cover media so that other cannot notice it. The characteristics of the cover media depends on the amount of data that can be hidden, the perceptibility of the message and its robustness. Publishing and broadcasting fields also require an Alternative solution for hiding information. Unauthorized copying is hot issue in the area like music, film, book and software. To overcome this problem some invisible information can be embedded in the digital media in such a way that no one can easily extract it. Analogously, software industries have taken advantage of another form of steganography, called watermarking, which is used to establish ownership, identification, and provenance. Image Steganographic Techniques Image steganography techniques can be divided into following domains. 1. Spatial Domain Methods: There are many versions of spatial steganography, all directly change some bits in the image pixel values in hiding data. Least significant bit (LSB)-based steganography is one of the simplest techniques that hides a secret message in the LSBs of pixel values without @IJRTER-2016, All Rights Reserved 341

introducing many perceptible distortions. Changes in the value of the LSB are imperceptible for human eyes. Spatial domain techniques are broadly classified into: 1. Least significant bit (LSB) 2. Pixel value differencing (PVD) 3. Edges based data embedding method (EBE) 4. Random pixel embedding method (RPE) 5. Mapping pixel to hidden data method 6. Labeling or connectivity method 7. Pixel intensity based method 8. Texture based method 9. Histogram shifting methods General advantages of spatial domain LSB technique are: 1. There is less chance for degradation of the original image. 2. More information can be stored in an image. Disadvantages of LSB technique are: 1. Less robust, the hidden data can be lost with image manipulation. 2. Hidden data can be easily destroyed by simple attacks. 2. Transform Domain Technique: This is a more complex way of hiding information in an image. Various algorithms and transformations are used on the image to hide information in it. Transform domain techniques are broadly classified into: 1. Discrete Fourier transformation technique (DFT). 2. Discrete cosine transformation technique (DCT). 3. Discrete Wavelet transformation technique (DWT). 4. Lossless or reversible method (DCT). 5. Embedding in coefficient bits. 3. Distortion Techniques: Distortion techniques need 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 adds a sequence of changes to the cover image. 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 use 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, the message bit is a 1. otherwise, the message bit is a 0. The encoder can modify the 1 value pixels in such a manner that the statistical properties of the image are not affected. 4. Masking and Filtering: These techniques hide information by marking an image, in the same way as to paper watermarks. These techniques embed the information in the more significant areas than just hiding it into the noise level. The hidden message is more integral to the cover image. Previous traditional hiding and encryption algorithms are discussed here. G. Naga Raju, James Vijay, presented a Secret-key based Separable Reversible Data-Hiding technique in Encrypted images(4). This method shows better results for data hiding in an image. Rahul Samant and Shrikant Agrawal, proposed a technique for Data Hiding in Gray-Scale Images using Pixel Value Differencing (5). Nagaraju G., and TV Hyma Lakshmi proposed a technique for image encryption which employs the concept of Secret-key images and SCAN patterns generated by SCAN methodology (7). This resulted in a highly distorted encrypted image. Y. K. Jain and R. R. Ahirwal proposed a technique Image Steganography Method With Adaptive Number of Least Significant Bits Modification Based on @IJRTER-2016, All Rights Reserved 342

Private Stego-Keys (13). By referring above references, a new approach is proposed for image hiding and encrypting. This is explained in next sessions. II. IMAGE HIDING AND RETRIEVAL A. Partitioning The Image: Cover image is decomposed into four parts (P1,P2,P3and P4) equal to the size of secret images as shown in the figure1.the decomposed is done in such way that the pixel values of each part will not be change. Figure1:Spiliting the Image B.Bit Splicing: In this project we are going to load an image file into MATLAB and slice it bitwise into 8 planes, then try to compress it. Each digital image consists basically of a number of pixels (rows x columns), each pixel has a specific intensity value, which is stored on the computer's memory as a binary number. Usually this binary number consists of 8 digits; for example 11111111 represents white, while 00000000 represents black. Separate it into 8 different images, each one is a bit layer. The each bit values of the all pixels will form a equivalent binary images. The binary image that form by taking all MSB s of pixels will slightly changes from the original image and further going to next bits the binary image will totally different from the original image. C. Image Hiding: The simplest of the LSB 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. The four secret images(i.e shown in figure 5) are encrypted by using secret key image, the resulted images are called hidden images. Encrypted images are hidden in the cover image by using LSB matching technique. Combine all the parts as single image called stego image. There is no visible difference between the two images. The difference being that the choice of whether to add or subtract one from the cover image pixel is random. D. Image Retrieval: For the secret image retrieval process the stego image is divided into four parts. The size of the each part will be equal to the original secret images. Then the encrypted images are recovered from the four parts of the stego image using LSB matching function. This encrypted images are converted into original secret images the decryption process is carried out. E. Image Decryption: The decryption process is simply the reverse process of encryption. In this process, the encrypted image containing hidden image is performed decryption algorithm with the key image. If the key entered at the time of decryption matches with that of encryption, original images are retrieved. Even if key do not match, decryption algorithm is performed but the decrypted image is a distorted one having no resemblance to the original image. But in both cases the recovered cover is same. @IJRTER-2016, All Rights Reserved 343

III. PROPOSED ALGORITHM Secret image hiding: Fig 2: Image Hiding and Encoding Cover image is decomposed into four parts (P1, P2, P3 and P4). Four hidden images are converted into black and white equivalent images. Perform Encryption process between each secret image and secret key image. Eight different images are formed by bit splicing, each part of the cover image. Encoded images are hidden in the cover image by using LSB matching technique. Combine all the parts as single image called stego image. Secret image extraction: Fig 3: Image Recover and Decoding Sizes of the hidden and key images are sent to the intended receiver via a secret communication channel. Stego image is decomposed into four parts (P1, P2, P3 and P4). Hidden images can recovered from the stego image using LSB matching function and knowing the size of the hidden image. Secret images are recovered from the hidden images by using Decryption algorithm. Secret images are recovered by using original secret key image are the original images. Secret images are recovered by using wrong secret key image are not the original images. In both cases the recovered cover is same. @IJRTER-2016, All Rights Reserved 344

IV. EXPERMENTAL RESULTS Cover image (figure4) is decomposed into four parts equal to the size of secret images. The four secret images are convert into black and white equivalent images as shown in figure 5. Perform Encryption process between each secret images and secret key image (as shown in figure 6) and results of this encryption process is shown figure 7. This four encryption images are combined into cover image by using LSB matching technique and recombine the all four parts as image called stego image as shown in the figure8. For secret images recovering process the stego image is decomposed into again four parts equal to the size of the secret images. The decryption process using original secret key image, the retrieved images are same as that of the original secret images as shown figure8. If we using a wrong secret key then the retrieved images are totally different the original secret images as shown in figure9.it clearly tell that, by using the wrong secret key the retrieved images are different from the original secret images. Encryption Process: V. RESULTS Figure 4: Cover Image Figure 5: Secret Images Figure 6:Secret Key Image Figure 7:Hidden Images @IJRTER-2016, All Rights Reserved 345

Figure 8:Stego Image Decryption process: Fig 8:Decryption Using Rightl Secret Key Image Fig 9:Decryption Using Wrong Secret Key Image VI. CONCLUSION & FUTURE SCOPE The main goal of this paper is to show how secret image can be embedded and how it can be sent through the internet by fooling grabbers. Many problems are encountered when transferring important data over the network. A safe and secure procedure is needed to transfer them easily. For this purpose simple image hiding techniques are used and the quality of stego images is also improved by using different mechanisms. So the hackers may not the stego image and will know nothing about the embedded secret image in it. The experimental results show that the stego image and the cover image remain more or less identical which is the main focus of this paper. This means that a secret message can be sent to the destination without any glitch and this can be used for image integrity protection and in places where important, undisclosed secrets should be sent to the recipient. Research is going on in privacy protection and intellectual property rights protection. In the future, it is expected to find an even better technique and procedure to hide more data in a cover image. The future focus should be made on even more less modification in the cover image and the differences between the cover image and the stego image should be null when statistically analyzed. @IJRTER-2016, All Rights Reserved 346

REFERENCES 1. Chi-Kwong Chan & L.M. Cheng (2001), Improved Hiding Data in Images by Optimal Moderately Significant- Bit Replacement, IEEE Electronics Letters, Vol. 37, No. 16, Pp.1017 1018. 2. K B Raja, Venugopal K R and L M Patnaik, "A Secure Stegonographic Algorithm using LSB, DCT and Image Compression on Raw Images",Technical Report, Department of Computer Science and Engineering, University Visvesvaraya College of Engineering,Bangalore University, December 2004. 3. S. Channalli and A. Jadhav, Steganography: an Art of Hiding Data, International Journal on Computer Science and Engineering, IJCSE, vol. 1, no. 3, (2009). 4. G. Naga Raju, James Vijay, Secret-key based Separable Reversible Data-Hiding in Encrypted image, National Conference on VLSI, Signal processing & Communications NCVSComs-2011. 5. Rahul Samant & Shrikant Agrawal (2011), Data Hiding in Gray-Scale Images using Pixel Value Differencing, Technology Systems and Management Communications in Computer and Information Science, Vol. 145, Pp. 27 33. 6. Gandharba Swain & Saroj Kumar Lenka (2012), A Technique for Secret Communication for New Block Cipher using Dynamic Stegnography, International Journal of Security and its Applications, Vol. 6, No. 2, Pp. 1 12. 7. G. Nagaraju and T. V. Hyma Lakshmi, Image encryption using secret-key images and SCAN patterns, International Journal in Advances in Computer, Electrical,& Electronics Engg., Vol. 02, 2012, pp. 13-18. 8. H. Yang, X. Sun and G. Sun, A High-Capacity Image Data Hiding Scheme Using Adaptive LSB Substitution, Journal: Radioengineering, vol. 18, no. 4, (2009),pp.509-516 9. Mohamed Radouane, Tarik boujiha, Rochdi messoussi, Nadia Idrissi & Ahmed Roukh (2013), A Method of LSB Substitution based on Image Blocks and Maximum Entropy, IJCSI International Journal of Computer Science Issues, Vol. 10, No. 1, Pp. 371 374. 10. Tarun Kumar, Karun Verma, A Theory Based on Conversion of RGB image to Grayimage, International Journal of Computer Applications Volume 7 No.2, September 2010. 11. Ramaraju PV, Nagaraju G, Chaitanya RK. Image Encryption and Decryption using Advanced Encryption Algorithm. Discovery, 2015, The International Daily journal, ISSN 2278 5469 EISSN 2278 5450, 29(107), Pp:2-28 12. Minati Mishra, A.R. Routray, M.C. Adhikary, Secured Steganography with Image Encryption through Chaotic Mapping, ANVESA, Vol-6, Issue 1&2, pp. 7-11, December 2011. 13. Y. K. Jain and R. R. Ahirwal, A Novel Image Steganography Method With Adaptive Number of Least Significant Bits Modification Based on Private Stego-Keys, International Journal of Computer Science and Security (IJCSS), vol. 4, (2010) March 1. 14. Gutte, R. S. and Chincholkar, Y. D. (2012) Comparison of Steganography at One LSB and Two LSB Positions, International Journal of Computer Applications, Vol.49,no.11, pp.1-7. 15. Dr. P.V.Rama Raju, T. Anvesh Gandhi, G. Naga Raju, RGB Image Steganography using Zigzag Pixel Indicator and Scan Techniques International Journal Of Research In Electronics And Computer Engineering., Vol. 3 Issue 3, July-Sept. 2015 ISSN: 2393-9028 (print) ISSN: 2348-2281 (online) Pp103-Pp107 16. Arvind Kumar, Km. Pooja, Steganography.A Data Hiding Technique International Journal of Computer Applications ISSN 09758887, Volume 9 No.7, November 2010. @IJRTER-2016, All Rights Reserved 347

Dr. P. V. RAMA RAJU Presently working as a Professor at the Department of Electronics and Communication Engineering, S.R.K.R. Engineering College, AP, India. His research interests include Biomedical-Signal Processing, Signal Processing, Image Processing, VLSI Design, Antennas and Microwave Anechoic Chambers Design. He is author of several research studies published in national and international journals and conference proceedings V. Sree lekha B.E in Electronics &Communication Engineering from S.R.K.R Engineering, Bhimavaram, A.P, India. M.Mubashirunnusa B.E in Electronics &Communication Engineering from S.R.K.R Engineering, Bhimavaram, A.P, India Presently working as assistant professor in Dept. of ECE, S.R.K.R. Engineering College, Bhimavaram, AP, India. He received B.Tech degree from S.R.K.R Engineering College, Bhimavaram in 2012, and M.Tech degree in Computer electronics specialization from Govt. College of Engg., Pune university in 2004. His current research interests include Image processing, digital security systems, Signal processing, Biomedical Signal processing, and VLSI Design Y.Manojkumar B.E in Electronics &Communication Engineering from S.R.K.R Engineering, Bhimavaram, A.P, India. M.VEERAMANIKANTA B.E in Electronics &Communication Engineering from S.R.K.R Engineering, Bhimavaram, A.P, India. @IJRTER-2016, All Rights Reserved 348