ISSN International Journal of Computer Technology and Electronics Engineering (IJCTEE) Volume 2, Issue 2 Web Based BPCS Steganography

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1 Web Based BPCS Steganography Sheetal Mehta, Kaveri Dighe, Meera Jagtap, Anju Ekre Abstract The technique to hide secret information in some other data (carrier) without any apparent evidence of data exchange is called as Steganography. Previously steganographic techniques have limited information-hiding capacity.50 60% Data can be hidden after implementation of this paper. This technique is called Bit Plane Complexity Segmentation (BPCS) Steganography. In the traditional steganograhy techniques principle was either to replace a special part of the frequency components of the carrier image, or to replace all the least significant bits of a multi-valued image with the secret information. Our new steganography uses an image as the carrier data, and we embed secret information in the bit-planes of the carrier. This technique makes use of the characteristics of the human vision system whereby a human cannot perceive any shape information in a very complicated binary pattern. We can replace all of the noise-like regions in the bit-planes of the carrier image with secret data without deteriorating the image quality. A typical carrier is a color image having Red, Green, and Blue color components in a multi-bit data structure. Index Terms steganography, data hiding, information hiding, BPCS, digital picture envelope, carrier image, bit plane. I. INTRODUCTION Our system integrates web applications, web services, client-server applications, application servers, and applications on the local client into a desktop environment using the desktop metaphor. The user can access functionality of Steganography services through client console. Steganography is defined as "hiding information within a noise; a way to supplement (not replace) encryption, to prevent the existence of encrypted data from being detected". Steganography and Cryptography are cousins in the data hiding techniques. Cryptography is the practice of scrambling a message to an obscured form to prevent others from understanding it. Steganography is the study of obscuring the message so that it cannot be seen. Fig 1 A Model Showing Communication 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. In recent years, several Steganographic programs have been posted on Internet home pages. Some of them use image data for the container of the secret information. Some of them use the least significant bits of the image data to hide the data. Other programs embed the secret information in a specific band of the spatial frequency component of the carrier. Some other programs make use of the sampling error in image digitization. However, all those Steganographic techniques are limited in terms of information hiding capacity. They can embed only 5-15 % of the vessel image at the best.. We termed our steganography BPCS-Steganography, which stands for Bit-Plane Complexity Segmentation Steganography. We made an experimental system to investigate this technique in depth. The merits of BPCS-Steganography found by the experiments are as follows. 1) The information hiding capacity of a true color image is around 50%. 2) A sharpening operation on the dummy image increases the embedding capacity quite a bit.. 3) Randomization of the secret data by a compression operation makes the embedded data more intangible. 4) Customization of a BPCS - Steganography program for each user is easy. It further protects against eavesdropping on the embedded information 5) It is most secured technique and provides high security. A. Objectives II. RELATED WORK Focus in this paper is towards information and data security during internet communication. 1) To provide the better data security. 2) Prevent form hacking. B. Algorithm Steps for the project are as follows : 1) Convert the carrier image(of any file format ) from PBC to CGC system and in png format. 2) Perform the histogram analysis. 3) After that bit-plane analysis is performed. 4) Perform size-estimation i.e. calcalate the places where we can store the secrete image. 5) Perform bit plane complexity segmentation on image i.e. embed secrete blocks into carrier image. 6) After embeding mail that image to another user. 7) For extracting the embedded image perform de-steganography which is exactly opposite to steganography. 126

2 III. ISSUES IN EXISTING SYSTEM Information send through any network have a chance to attack by hackers.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. Furthermore, in many cases it is desirable to send information without anyone even noticing that information has been sent secret information. IV. PROPOSED SYSTEM 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. All of the traditional steganographic techniques have limited information-hiding capacity. They can hide only 10% (or less) of the data amounts of the vessel. This Technique uses an image as the vessel data, and we embed secret information in the bit-planes of the vessel. We can replace all of the noise-like regions in the bit-planes of the vessel image with secret data without deteriorating the image quality We termed our steganography BPCS-Steganography, which stands for Bit-Plane Complexity Segmentation [ 14] V. MECHANISM I..Bit-Plane Decomposition of a Multi-Valued Image : A multi-valued image (M) consisting of n-bit pixels can be decomposed into a set of n binary pictures. For example, if the image is an n-bit gray image, it is shown as, M= (M1, M2,..., Mn) As far as the bit- planes of a natural image are concerned, complexity of each bit-plane Fig 2. Bit-Plane pattern increases monotonically from the MSB (M1) to the LSB (Mn). An image data not having this property will be an artificially processed data. Most of the LSB planes look like random pattern. II. Two Binary Number Coding Systems: PBC and CGC are related by the following Exclusive OR operation. In BPCS-Steganography embedding operation is executed after the carrier image has been transformed from PBC to CGC. III. Use of Nature of Human Vision: Replace each noise-looking region with another noise-looking patterns without changing the overall quality. See Fig 3 Before embedding After embedding Fig 3. Embedding a "noisy" square in the bottom right corner of PR6[1] IV. Extraction of secrete image : The embedded image is finally extracted from carrier image with the help of de-steganography method which is exactly opposite to steganography method. VI. SYSTEM ARCHITECTURE CLIENT 1 Origional image MG3 MG5 MG7 Fig.2 bit plane decomposition. In case the image is a Red, Green, Blue color picture, it is shownby M=(MR1,MR2,..,MRn,MG1,MG2,..,MGn,MB1,MB2,..,MB n ) Where MR1, MG1, MB1 are the most significant bit-planes (MSB), while MRn, MGn, MBn are the least significant planes (LSB). Ordinary image data is represented by a Pure Binary Code system (referred to as PBC which is commonly used in image processing). It is also possible to use other code systems such as Canonical Gray Code (CGC). CGC is better than PBC for BPCS-Steganography. CLIENT 2 CILENT 3 KEEP LOG OF RECEIVING SENDING EXTRACT IMAGE ENCODING DECODING Fig.4 Data Flow diagram. EMBEDIND SEND VIA SERVER 127

3 The data flow diagram for this paper is as shown in fig 4.This paper implements a client server application where number of clients can work at a time. Along with the BPCS steganography they can they can perform various functions such as A. File conversion: A. File conversion B. Histogram. C. Size estimation. D. Bpcs steganography.. E. Mailing. F. De-steganography. a. Portable Network Graphics - PNG The PNG compression algorithm is one of the best that can be found. Unlike standard JPEG images, PNG compression involves no loss of image data, so there is no smudging or blurring.nearly all the latest browsers support PNG's variable transparency, including WebTV and Microsoft Internet Explorer for Macs PNG format allows all kinds of extra information to be stored inside image files. The two most potentially helpful features for web images are gamma correction and embedded text. Portable Network Graphics format was originally devised at a time when there was no browser support for GIF animation, so animation was not included in the specification. B. Histogram: Histograms are functions describing information extracted form the image.the histogram function is defined over all possible intensity levels. For each intensity level, its value is equal to the number of the pixels with that intensity. C. Size estimation: In size estimation we have to calculate the regions where maximum color variations are observed. After doing this we have to store pixel value of secret image at that variation regions.while doing so we use the concept of embading capacity. For a given image, embedding capacity can be traded with image quality by altering the complexity threshold. If image used has a threshold of 24 border pixels per 8 8 region; so regions having more border pixels than this were eligible for embedding.[4] D. BPCS Steganography: Here the actual steganography is performed. In our method we call a carrier image a carrier. It is a color image in BMP file format, which hides (or,embeds) the secret information (files in any format). We segment each secret file to be embedded into a series of blocks having 8 bytes of data each. These blocks are regarded as 8 8 image patterns. We call such blocks the secret blocks. We embed these secret blocks into the vessel image using the following steps. 1) Convert the carrier image from PBC to CGC system i.e. convert file from any format into png format. 2) Segmentation on carrier image is performed i.e. each bit-plane of the carrier image into informative and noise-like regions by using a threshold value (α0).that means complexity of image is calculated. 3) Group the bytes of the secret file into a series of secret blocks. 4) If a block is less complex than the threshold (α0), then conjugate it to make it a more complex block. 5) The conjugated block must be more complex than α0. 6) Embed each secret block into the complex regions of the bit-planes (or, replace all the noise-like regions with a series of secret blocks) where maximum color changes are observed. 7) Convert the embedded dummy image from CGC back to PBC.[1][2] Bit Plane Slicing Concept in BPCS: Fig. 5 Original image[16] Here we are using the concept of bit plane slicing. The bit plane slicing can be better understood with the help of fig8..the operation of splitting the image into its constituent binary planes is called Bit plane slicing. Pixels are digital numbers composed of bits. In an 8-bit image, intensity of each pixel is represented by 8-bits. The 8-bit image is composed of eight 1-bit plane regions from bit plane 0 (LSB) to bit-plane 7 (MSB). Plane 0 contains all lowest order bits of all pixels in the image while plane 7 contains all higher order bits. Bit plane Slicing is useful for image compression. Complexity of each bit plane pattern increases monotically from MSB to LSB. Fig 6 Graph of the histogram function[ 16] 128

4 V. Mailing: CREATE AN ENVIRON MENT FOR MAILIG Fig 7 bite plan concept[15] USER 1 WIIL SEND RESULT OF BPCS USER 2 WILL LOAD IT EXTRACT THE INFORMATI ON VII. APPLICATIONS 1) The more obvious applications of BPCS Steganography relate to secret communications. 2) The presence of the embedded data may be known, and the software for extraction and embedding can be standardized to a common set of customization parameters. An example of this is a digital photo album, where information related to a photo, such as date and time taken, exposure parameters, and scene content, can be embedded in the photo itself. 3) To have secure secret communication where strong cryptography is impossible. 4) In some cases, like in military applications, even the knowledge that two parties communicate can be of large importance. 5) The health care, and especially medical imaging systems, may very much benefit from information hiding techniques. VII. ADVANTAGE/SCOPE 1) Tography, DeStagnography, Mail, and File Format Conversion on a thin client. 2) Less prone to typical attacks, viruses, worms, unpatched clients, vulnerabilities 3) Sensitive data stored on secure servers rather than scattered across multiple potentially unprotected and vulnerable clients (e.g. smart phones and laptops) 4) Encrypted transmission of all data between server and clients. 5) Software Management features (above) accommodate quick and easy application of security advisories on server side VIII. CONCLUSION Fig. 8 Mailing. In mailing we create an environment just like yahoo or rediff and send r image from one user to other.after receving the image form user one user two loades that image and extract the hidden data from it by performing de-steganography VI. De-steganography: De-steganography is exactly opposite of steganography.here we will extract secret image from vessel image.in this way we will get the secret image form hiding it from the third person.[2] From the overall study of the project details, the certain facts that how marketing is done on the basis of Ranking System. Here we are providing data to the particular search engines. The ranks of the tags are level wise displayed on the website so that the customer or user is able to understand how the ranking system works. For Ranking we used cohesion based Hierarchical Clustering technique. Apart from using Crawling or Direct Access to database technique, we have shown the benefits of our technique. It are because this technique is used basically for this application only. It is efficient to use and the output is obtained very fast within a micro second. Various users visit the websites through various tags in a second. So this system also deals with handling of various users at a time as well as the working of Hierarchical Clustering. 129

5 The objective of this paper was to demonstrate our BPCS-Steganography, which is based on a property of the human visual system. The most important point for this technique is that humans can not see any information in the bit-planes of a color image if it is very complex. We have discussed the following points and showed our experiments. 1) We can categorize the bit-planes of a natural image as informative areas and noise-like areas by the complexity thresholding. 2) Humans see informative information only in a very simple binary pattern. 3) We can replace complex regions with secret information in the bit-planes of a natural image without changing the image quality. This leads to our BPCS-Steganography. 4) Gray coding provides a better means of identifying which regions of the higher bit planes can be embedded. 5) A BPCS-Steganography program can be customized for each user. Thus it guarantees secret Internet communication. We are very convinced that this steganography is a very strong information security technique, especially when combined with encrypted embedded data. Furthermore, it can be applied to areas other than secret communication. Future research will include the application to vessels other than 24-bit images, identifying and formalizing the customization parameters, and developing new applications. [15] ENEE408G Multimedia Signal Processing (fall 03) Overview of MATLAB Programming [16] ASAM - Image Processing 2008/2009. Lecture 5 AUTHOR PROFILE Sheetal Mehta: id:shitzmehta@gmail.com Kaveri Dighe: id:kavyadighe30@gmail.com Meera Jagtap: id:meerajagtap96@gmail.com Anju Ekre: id: anjuekre@gmail.com REFERENCE [1] N. Johnson and S. Jajodia, (Feb 1998): Exploring steganography: seeing the unseen, IEEE Computer, pp [2] A.Habes, (Feb 2006): Information Hiding in BMP image Implementation, Analysis and Evaluation, Information Transmission in Computer Networks. [3] E. T. Lin and E. J. Delp: A Review of Data Hiding in Digital Images, Video and Image Processing Laboratory, Indiana. [4] S.G.K.D.N. Samaratunge, (August 2007): New Steganography Technique for Palette Based Images, Second International Conference on Industrial and Information Systems, ICIIS [5] Yeaun-Keun Lee and Ling-hwei Chen: Secure Error-Free Steganography for JPEG Images. [6] R.J. Anderson, F.A.P. Peticolas, (May 1998): On the Limits of Steganography, IEEE Journal of Selected Areas in communication. [7] A. Habes, (Dec 2005): 4 Least Significant Bits information Hiding Implementation and Analysis, GVIP 05 Conference, CICC,Cairo, Egypt. [8] Eiji Kawaguchi, Richard O. Eason: Principle and applications of BPCS Steganography. [9] Michiharu Niimi, Hideki Noda and Eiji Kawguchi, (1997): An image embedding in image by a complexity based region segmentation method IEEE. [10] KIT Steganography Research Group: Principle of BPCS Steganography, Japan. [11] Rafael C. Gonzalez, Richard E. Woods: Digital Image Processing, Third Edition, Pearson Education, pp [12] Hioki Hirohisa: A Data Embedding method using BPCS principle with new Complexity measures. [13] ENEE408G Multimedia Signal Processing (fall 03) Overview of MATLAB Programming [14] E. T. Lin and E. J. Delp: A Review of Data Hiding in Digital Images, Video and Image Processing Laboratory, Indiana. 130