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International Journal of Computer Information Systems, Vol.4, No 3, 2012 ECC Based Secure Large Size Data Transmission over Fraudulence Network Shubhi Gupta P. S. Gill M.Tech. Scholar, Deptt. of Computer Science & Professor, Deptt. of Computer Science & Engineering, Engineering, Krishna Engineering College, Krishna Engineering College, Ghaziabad, U.P. (India), Ghaziabad, U.P. (India), e-mail: sr23.shubhi@gmail.com e-mail: pavittergill@hotmail.com Abstract— In this paper, we present a secured scheme of any large size data transmission over fraudulence network. In this II. PRELIMINARIES approach we use Steganography and compression technique with A. Steganography ECC cryptosystem to enhance the security of data to be transmitted over insecure channel. A complete transmission of Steganalysis is a technology which determines the data is based upon correctness and delivery on time, so we use presence of a hidden message or image in cover image and Fuzzy error correction code for error less message over attempt to disclose the actual contents of this message [4].A fraudulence network. more erudite method of steganography is by merging the two techniques to produce more security to secure data Keywords- Steganography, SEQUITUR Compression Algorithm, transmission such that if intruders detect the presence of data ECC cryptosystem, Image File, Error Correction Code. even then message cannot be decode without the knowledge of key. I. INTRODUCTION The most common stegno method is the LSB approach, or Cryptography is a branch of applied mathematics that aims Least Significant Bit. As we know digital pixels are to add security in the ciphers of any kind of messages. represented by three colors: red, green and blue. These colors Cryptography algorithms use encryption keys, which are the together form digital pictures or video. Each color of every elements that turn a general encryption algorithm into a pixel requires 1 byte or 8 bits of information. Since the first bit specific method of encryption. The data integrity aims to is the “least significant” or carries the least amount of verify the validity of data contained in a given document. [1] importance in the byte, this steganographic technique chooses Steganography is a technique used to embed secret to overwrite the first bit of successive bytes until the entire information into non-secret information, preventing the secret message is embedded into the original source file, or the message from being detected by non-authorized people. [2] cover data. Since we have only modified the least significant To reduce the size of sending files, a compression scheme bits of a portion of the source file, the human eye should not can be employed what is known as lossless compression on be able to detect the degradation in the picture or video [5]. secrete message to increase the amount of hiding secrete data, The purpose of steganography is to hide the very presence a scheme that allows the software to exactly reconstruct the of communication by embedding messages into original message [3]. innocuous-looking cover objects, such as digital images. To Fraudulence network is a growing problem in this modern accommodate a secret message, the original cover image is era. There are many unauthorized users who can try to access slightly modified by the embedding algorithm to obtain the information by using the internet. Fraudulence is the technique stego image. The embedding process usually incorporates a used by unauthorized users to get information about secret stego-key that governs the embedding process and it is transmitted data of another user from the network. Internet is also needed for the extraction of the hidden message [6]. most common way for any kind of data transmission over the There are three basic views behind hiding information. The network in this modern era. Every user wants the security of first is capacity, which is the amount of information that can his data, because the numbers of internet users are increased be embedded within the cover file. An information-hiding by day to day, and there are also, many unauthorized users algorithm has to be able to compactly store a message within a who want to get another’s personal information. So, the file. Next is security, which refers to how a third-party can security of any personal information from these unauthorized detect hidden information within a file. Intuitively, if a users is the big problem. message is to be hidden, an ideal algorithm would store information in a way that was very hard to notice. High security layers have been proposed through three layers to make it difficult to break through the encryption of the input March Issue Page 27 of 68 ISSN 2229 5208 International Journal of Computer Information Systems, Vol.4, No 3, 2012 data and confuse steganalysis too. Various encryption 6. Bob decrypts by calculating M = C2 - d×k×P techniques like cryptography, digital watermarking, M = C2 - d×k×P = M + k×Q - d×k×P = M + k×Q - steganography etc have already been introduced in attempt to d×Q = M. address these growing concerns [7]. Steganography have four application areas: C. Data Compression Copyright Protection- It has security, invisibility and A compression scheme can be employed what is known as robustness requirements. Watermark techniques fit in lossless compression on secrete message to increase the this area. amount of hiding secrete data, a scheme that allows the Authentication- It has security and invisibility software to exactly reconstruct the original message [12]. requirements. Digital signature fits in this area. The transmission of numerical images often needs an Secret and Invisible Communication- It has requirements important number of bits. This number is again more for security, invisibility and insertion of high volumes of consequent when it concerns medical images. If we want to secret data. [8] transmit these images by network, reducing the image size is important. The goal of the compression is to decrease this B. The ECC Public-Key Cryptosystem initial weight. This reduction strongly depends of the used Elliptic Curve Cryptography (ECC) [9, 10] is a public key compression method, as well as of the intrinsic nature of the cryptography. In public key cryptography, each user or the image. Therefore the problem is the following: device taking part in the communication generally have a pair 1. To compress without lossy, but with low factor of keys, a public key and a private key, and a set of operations compression. If you want to transmit only one image, it is associated with the keys to do the cryptographic operations. satisfactory. But in the medical area these are often sequences The mathematical operations of ECC is defined over the that the doctor waits to emit a diagnostic. elliptic curve y2 = x3 + ax + b, where 4a3 + 27b2 ≠ 0. 2. To compress with losses with the risk to lose information. Each value of the ‘a’ and ‘b’ gives a different elliptic curve. The question that puts then is what the relevant information is’s All points (x, y) which satisfies the above equation plus a to preserve and those that can be neglected without altering the quality of the diagnosis or the analysis. The human visual point at infinity lies on the elliptic curve. The public key is a system is one of the means of appreciation, although subjective point in the curve and the private key is a random number. The and being able to vary from an individual to another. However, public key is obtained by multiplying the private key with the this system is still important to judge the possible causes of generator point G in the curve. The generator point G, the degradation and the quality of the compression [13]. curve parameters ‘a’ and ‘b’, together with few more constants constitutes the domain parameter of ECC. D. The SEQUITUR Algorithm The SEQUITUR algorithm represents [14] a finite sequence _ as a context free grammar whose language is the singleton set {}. It reads symbols one-by-one from the input sequence and restructures the rules of the grammar to maintain the following invariants: (A) no pair of adjacent symbols appear more than once in the grammar, and Figure1: An Elliptic curve. (B) every rule (except the rule defining the start symbol) is used more than once. To intuitively understand the algorithm, Operation we briefly describe how it works on a sequence 123123. As For curve y2 = x3 + ax + b usual, we use capital letters to denote non-terminal symbols. 1. Elliptic Curve Point Addition. After reading the first four symbols of the sequence 123123, Point Addition P(x1,y1) ≠Q(x2,y2). the grammar consists of the single production rule S 1, 2, 3, Point Doubling P(x1,y1) 1 where S is the start symbol. On reading the fifth symbol, it 2. Elliptic Curve Scalar Multiplication. becomes S 1, 2, 3, 1, 2 Since the adjacent symbols 1, 2 It computes k×P for a given point P and appear twice in this rule (violating the first invariant), integer k. Q = k×P = (P + P + … + P) ((k-1) SEQUITUR introduces a non-terminal A to get addition) S A, 3, A A 1, 2 Elliptic Curve Cryptosystem [11] Note that here the rule defining non-terminal A is used twice. 1. Bob chooses the curve E and point P on the curve Finally, on reading the last symbol of the sequence 123123 the 2. Bob chooses integer d and calculates Q = d×P and above grammar becomes makes it public S A, 3, A, 3 A 1, 2 3. Alice maps the plaintext m to point M on curve This grammar needs to be restructured since the symbols 4. Alice chooses a random integer k A, 3 appear twice. SEQUITUR introduces another non- 5. Alice encrypts M as C1 = k×P , C2 = M + k×Q terminal to solve the problem. We get the rules March Issue Page 28 of 68 ISSN 2229 5208 International Journal of Computer Information Systems, Vol.4, No 3, 2012 S B, B BA3 A 1 2 follows: However, now the rule defining non-terminal A is used only once. So, this rule is eliminated to produce the final Phase 1. Process for encrypting the original message result. Step 1: Choose the curve E and point P on the curve. S B, B B 1, 2, 3 Step 2: Chooses integer d and calculates Q = d×P and makes it Note that the above grammar accepts only the sequence public. 123123. Step 3: Maps the plaintext m to point M on curve. Step 4: Choose a random integer k. E. Error Correction Code Step 5: Encrypts plain text M as ciphertexts C1 = k×P, C C2 = M + k×Q. A metric space is a set with a distance function dist : C C R [0, ) , which obeys the Phase 2. Process to compress the encrypted message usual properties(symmetric, triangle inequalities, zero distance Step: Perform the lossless compression technique (sequitur) on between equal points)[15,16]. cipher text to increase the amount of hiding secrete data. n Definition: Let C{0,1} be a code set which consists of a set Phase 3. Process for convert cover image file c Step 1: Generating blocks of code words i of length n. The distance metric between any In RGB space the image is split up into red, blue and green ci cj C images. The image is then divided into blocks of pixels two code words and in is defined by n and accordingly the image of pixels will contain dist (ci , c j ) cir c jr ci , c j C blocks. Where, , . r 1 This is known as Hamming distance [17]. Step 2: DCT All values are level shifted by subtracting 128 from each Definition: An error correction function f for a code C is value. The Forward Discrete Cosine Transform of the block is defined as then computed. The mathematical formula for calculating the f (ci ) {c j / dist (ci , c j ) is the minimum, over C {ci }} DCT is: . Here, c j f ci c is called the nearest neighbor of i [15]. Definition: The measurement of nearness between two code words c and c is defined by Where, nearness (c, c) dist (c, c) / n , it is obvious that 0 nearness (c, c) 1 [17]. Definition: The fuzzy membership function for a codeword Where c to be equal to a given c is defined as [15] FUZZ (c) 0 if nearness(c, c) z z 0 1 Step 3: Quantization z otherwise Quantization is the step where the most of the compression takes place. DCT really does not compress the image, as it is III. OUR SCHEME almost lossless. Quantization makes use of the fact that, the In our approach, we use ECC cryptosystem to encrypt the high frequency components are less important than the low original message which involves certain mathematical frequency components. The Quantization output is operations. Then we use a compression technique and sequitur compression algorithm on encrypted data to hide the large amount of data with high security. Steganography algorithm The matrix could be anything, but the JPEG i.e. Least Significant Bit (LSB) coding, is used to hide the committee suggests some matrices which work well with compressed and encrypted data into cover image file. Least image compression. Significant Bit (LSB) coding is the way, to embed information into the cover image file. Here we also use the Error Step 4: Compression using SEQUITUR Correction Code to detect and correct the errors occurred After quantization, the scheme uses a filter to pass only the during the transmission. This method is really appreciable to string of non-zero coefficients. By the end of this process we provide high security. will have a list of non-zero tokens for each block preceded by ECC is the asymmetric key cryptosystem which provides their count. the same level of security with smaller keys than other public DCT based image compression using blocks of size 8x8 is key cryptosystems. The whole process of proposed work is as considered. After this, the quantization of DCT coefficients of March Issue Page 29 of 68 ISSN 2229 5208 International Journal of Computer Information Systems, Vol.4, No 3, 2012 image blocks is carried out. The SEQUITER compression is FUZZ (c) 0 if nearness(c, c) z z 0 1 then applied to the quantized DCT coefficients. z otherwise Phase 4. Process to embed confidential message into cover image file. IV. SECURITY ANALYSIS Algorithm to embed confidential message into cover image In this proposed method we use ECC Cryptosystem to file named inFile generate new file with embedded message make secure transmission of any large size data over the file named outFile. Encoded-Message (msg,inFile on input- fraudulence network, because ECC is one of the public key mode, outFile on output-mode) cryptosystem that provides same level of security with smaller keys. Here, we use Steganography, Compression technique Step 1: Read offset bytes from input inFile and writes to with sequitur algorithm and Error correction code with ECC output File outFile cryptosystem to get highly secured data. When the encoded message c is transmitted over the Step 2: Calculate message length and write it into output file fraudulence network, it is possible that during the transmission by embedding using XOR function it in last two bits for every some bits of c can be changed and the receiver receives the byte. Suppose, Message length being 16 bits, will be stored in incorrect message c’. He calculates that dist(x, y) is 8 pairs of 2 bits. minimum. If the error is not too large, that is , Step 3: Embed each byte of message in 4 pairs of 2 bits each is where d is the minimum distance of any two distinct code embedded in 4 byte of input file and written into output file words, then c’ is equal to the original message c. named outFile. V. CONCLUSION Step 4: Write the remaining bytes of the input file into output In this paper, we present an effective scheme by using the file. LSB matching method to embed secure data into the stegno-image to transmit large data over the fraudulence Phase 5. Process to generate message from Image network. This proposed approach uses Steganography, ECC The picture is received at receive side. This function decode cryptosystem, Lossless Compression–Sequitur algorithm and message from a file named outFile open on output mode. Error Correction Code – Fuzzy error correction code to provide Decode Message (outFile on Input-mode) high security for large data over fraudulence network during Step 1: Read offset bytes from the input file and apply the transmission. again XOR function, Generate message bit. Step 2: Read last 2 bits of consecutive 8 bytes and REFERENCES concatenate them to get the message length. [1] Diego F. de Carvalho, Rafael Chies, Andre P. Freire, Luciana A. F. Martimiano and Rudinei Goularte, “Video Steganography for Step 3: Read last 2 bits from input file in pairs of 4 and Confidential Documents: Integrity, Privacy and Version Control” , concatenate them to get message of 1 byte. University of Sao Paulo – ICMC, Sao Carlos, SP, Brazil, State University of Maringa, Computing Department, Maringa, PR, Brazil. Step 4: Repeat step 3 until the message is extracted of [2] Niels Provos, Peter Honeyman, Hide and Seek: Introduction to calculated length. Steganography, IEEE Security and Privacy, Volume 1 , Issue 3 (May 2003), Pages: 32 - 44 Step 5: Decompress & Decrypt the message. [3] Nameer N. EL-Emam, “Hiding a Large Amount of Data with High Decrypts by calculating M = C2 - d×k×P. Security Using Steganography Algorithm” Applied Computer Science Department, Faculty of Information Technology, Philadelphia M = C2 - d×k×P = M + k×Q - d×k×P = M + k×Q - d×Q = M. University, Jordan [4] Nameer N. EL-Emam, Hiding a Large Amount of Data with High Phase 6. Process for detection and correction of error Security Using Steganography Algorithm Applied Computer Science Department, Faculty of Information Technology, Philadelphia If any error occurred during the transmission of message, University, Jordan we can detect and correct using fuzzy error correcting code. [5] Alain C. Brainos, A Study Of Steganography And The Art Of Hiding Information, East Carolina University, Receiver check that dist (t (c)c ) 0 , he will realize that there , http://www.infosecwriters.com/text_resources/pdf/steganographyDTEC 6823.pdf is an error occur during the transmission. Receiver apply the , [6] Jessica Fridrich and Miroslav Goljan, Digital image steganography error correction function f to c : f (c) . using stochastic modulation, Department of Electrical and Computer Engineering, SUNY Binghamton, Binghamton, NY, 13902-6000, USA. Then receiver will compute [7] Swarnendu Mukherjee, Swarnendu Bhattacharya, Amlan Chaudhury nearness (t (c), f (c, )) dist (t (c) f (c, )) / n Triple Layer Data Security ACM Ubiquity, Volume 9, Issue 17, April 29-May 5 ,2008 [8] Zhao, J. In business today and tomorrow, ACM Communications of the ACM, p. 7, 1998. March Issue Page 30 of 68 ISSN 2229 5208 International Journal of Computer Information Systems, Vol.4, No 3, 2012 [9] Certicom, Standards for Efficient Cryptography, SEC 1: Elliptic Curve [14] N.Walkinshaw, S.Afshan, P.McMinn ”Using Compression Algorithms Cryptography, Version 1.0, September 2000. to Support the Comprehension of Program Traces” Proceedings of the [10] Certicom, Standards for Efficient Cryptography, SEC 2: Recommended International Workshop on Dynamic Analysis (WODA 2010) Trento, Elliptic Curve Domain Parameters, Version 1.0, September 2000. Italy, July 2010. [11] A. Hosseinzadeh Namin, Elliptic Curve Cryptography, RESEARCH [15] J.P.Pandey, D.B.Ojha, Ajay Sharma, “Enhance Fuzzy Commitment CENTRE FOR INTEGRATED MICROSYSTEMS–UNIVERSITY OF Scheme: An Approach For Post Quantum Cryptosystem”, in Journal of WINDSOR, April 2005. Applied and Theoretical Information Technology, (pp 16-19 ) Vol. 9, No. 1, Nov. 2009. [12] Nameer N. EL-Emam, “Hiding a Large Amount of Data with High Security Using Steganography Algorithm” Applied Computer Science [16] V.Pless, “ Introduction to theory of Error Correcting Codes”, Wiley, Department, Faculty of Information Technology, Philadelphia New York 1982. University, Jordan [17] A.A.Al-saggaf,H.S.Acharya,“A Fuzzy Commitment Scheme”IEEE [13] Borie J., Puech W., and Dumas M., “Crypto-Compression System for International Conference on Advances in Computer Vision and Secure Transfer of Medical Images”, 2nd International Conference on Information Technology 28-30November 2007–India. Advances in Medical Signal and Information Processing (MEDSIP 2004), September 2004. March Issue Page 31 of 68 ISSN 2229 5208

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