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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             BA3              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
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                                                                            Department, Faculty of Information Technology, Philadelphia
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        March Issue                                           Page 30 of 68                                          ISSN 2229 5208
                                                                                      International Journal of Computer Information Systems,
                                                                                                                            Vol.4, No 3, 2012
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         March Issue                                                  Page 31 of 68                                         ISSN 2229 5208

				
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