ANALYSING SECURE IMAGE SECRET SHARING SCHEMES BASED ON STEGANOGRAPHY by iaemedu

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									  International Journal of JOURNAL OF COMPUTER (IJCET), ISSN 0976-
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  ANALYSING SECURE IMAGE SECRET SHARING SCHEMES BASED
                   ON STEGANOGRAPHY

                       Sonali Patil 1, Kapil Tajane 2, Janhavi Sirdeshpande 3
           1
               (Research Student, Sant Gadge Baba Amravati University, Amravati, India)
         2, 3
               (ME Student, Pimpri Chinchwad College of Engineering, Nigdi, Pune, India)


  ABSTRACT

          The idea of secret sharing is to start with a secret, divide it into pieces called shares,
  which are then distributed amongst participants by the dealer. Only certain authorized subsets
  of participants can reconstruct the original secret. Visual Cryptography is a technique in
  which a secret is encrypted into several image shares/shadows and then decrypted later using
  a human visual system to stack all the share images. Conventional visual Cryptography
  methods divide a secret image into n shares and distribute these shares to n participants. But
  the created shadows are meaningless which can attract the attacker’s attention. Applications
  for secret sharing schemes seem to be getting more important now a days. For many
  circumstances, secret sharing has to provide more security as per the need of an application.
  To remedy such kind of vulnerabilities embedding of shadows can be a solution. The
  shadows can be embedded in cover images which make them more secure. The intent of this
  paper is to explain how the combination of secret sharing and steganography makes the secret
  sharing scheme more secure. The four different secret sharing schemes based on
  steganography to support the security of scheme. The comparative study of these methods
  guides to select a scheme and also proposes need of future to make such schemes stronger.

  Keywords: Cryptography, Secret Sharing, Security, Steganography

  I. INTRODUCTION

         Due to fast growth of Internet applications, digitized data becomes more and more
  popular. Secure transmission of data is more and more needed in the worldwide computer
  network environment. The effective and secure protections of sensitive information are
  primary concerns where only encrypting data is not a solution. Data security becomes an
  important issue nowadays. In certain applications, it is a risk if a set of secret data is held by
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6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 2, March – April (2013), © IAEME

                                                                                incidentally
only one person without extra copies because the secret data set may be lost incidentall or
modified intentionally. Secret Sharing Schemes refers to method for distributing a secret
amongst a group of participants, each of whom is allocated a share of the secret. The secret
                                                                          combined
can be reconstructed only when a sufficient number of shares are combined together;
individual shares are of no use on their own. Shamir [1] introduced a secret sharing in 1979.
1.1 Visual Cryptography
                                          secret sharing
       Visual cryptography (VC) is a secret-sharing scheme that uses the human visual
system to perform the computations. Naor and Shamir introduced Visual Cryptography (VC)
            .
in 1994 [2]. They asked the following intriguing question: is it possible to devise a secret
sharing scheme in which an image can reconstructed "visually" by superimposing two
shares? Each share would consist of a transparency, made up of black and white pixels.
Examination of one share should reveal no information about the image. Naor and Shamir
devised the scheme that specifies how to encode a single pixel, and it would be applied for
                      ge
every pixel in the image to be shared. This scheme is illustrated in the Fig. 1.




                                  Fig 1. Visual Cryptography

A pixel P is split into two sub pixels in each of the two shares. If P is white, then a coin toss
                                                                     above.
is used to randomly choose one of the first two rows in the figure above. If P is black, then a
coin toss is used to randomly choose one of the last two rows in the figure above. Then the
pixel P is encrypted as two sub pixels in each of the two shares, as determined by the chosen
                                  encrypte
row in the figure. Every pixel is encrypted using a new coin toss.
Suppose we look at a pixel P in the first share. One of the two sub pixels in P is black and the
                                                           "black white"
other is white. Moreover, each of the two possibilities "black-white" and "white"white-black" is
                                         whether
equally likely to occur, independent of whether the corresponding pixel in the secret image is
black or white.
Thus the first share gives no clue as to whether the pixel is black or white. The same
argument applies to the second share. Since all the pixels in the secret image were encrypted
using independent random coin flips, there is no information to be gained by looking at any
group of pixels on a share, either. This demonstrates the security of the scheme.

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International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 2, March – April (2013), © IAEME

1.2 Steganography

       Image embedding hides a secret message in a cover image, this process is usually
parameterized by a hide-key, and the detection or reading of embedded information is
possible only by having this key.

1.2.1 Least Significant Bit Insertion [4]

       In this method the secret message is embedded into the least significant bit plane of
the image. Since this only affects each pixel by +/- 1, if at all, it is generally assumed with
good reason that the degradation caused by this embedding process would be perceptually
transparent. Hence there are a number of LSB based Steganography techniques available in
the public domain. The problem with this method is that it does not provide protection against
small changes resulting from lossy compression or image transformations. The other
disadvantage of this method is that it is having very less data hiding capacity.

1.2.2 Adaptive MELSBR Method [3]

        To avoid changing the properties of cover-images, the message must be embedded in
"random texture" areas of each bit-plane. For taking advantage of local characteristics, an
adaptive Steganography method based on the Minimum Error LSB Replacement (MELSBR)
method is proposed. First, the upper bound of embedding capacity for each pixel in the cover-
image is evaluated. If the amount of message to be embedded is less than the total embedding
capacity provided by the cover-image, whole secret message will be embed in a local area
and it can be easier for the attacker to extract the secret. To treat this scattering method is
provided.

1.2.3. Bit Plane Complexity Segmentation (BPCS): [4]

        BPCS steganography was introduced by Eiji Kawaguchi and Richard O. Eason, to
overcome the short comings of traditional steganographic techniques such as Least
Significant Bit (LSB) technique, Transform embedding technique, Perceptual masking
technique. This traditional technique has limited data hiding capacity and they can hide up to
10 – 15% of the vessel data amount. BPCS steganography makes use of important
characteristic that of human vision. In BPCS, the vessel image is divided into “informative
region” and “noise-like region” and the secret data is hidden in noise blocks of vessel image
without degrading image quality . In LSB technique, data is hidden in last four bits i.e. only
in the 4 LSB bits . But in BPCS technique, data is hidden in MSB planes along with the LSB
planes provided secret data is hidden in complex region.
        Various secret sharing techniques have been developed to secure data, but there is a
need to add more security to created shares as the shares are meaningless which can add
attacker’s attraction. The created shares can be embedded in cover images to make the shares
meaningful.
        Very few researchers have proposed the combination of secret image sharing and
hiding techniques. These techniques give higher reliability and security at the same time
compared to only sharing or only hiding techniques. Chin-Chen Chang and Duc Kieu [7]
have proposed a novel secret sharing and information-hiding scheme by embedding a secret
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6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 2, March – April (2013), © IAEME

image and a secret bit stream into two shadow images. It has limited reliability and shadow
image size is more. Y.S. Wu, C.C. Thien, and J.C. Lin [10] have proposed sharing and hiding
of secret images but with size constraint. Wang’s [11] verifiable secret sharing method is
used to create the shares/shadows for binary images. This paper discusses few secret sharing
schemes based on steganography.
   The rest of the paper is organized as follows. In Section 2 some definitions are discussed.
Section 3 covers literature survey based on secret sharing schemes and steganography.
Section 4 discusses the comparison of the schemes discussed in literature survey. Finally in
section 5, the survey is summarised based on their comparative results.

II. SOME DEFINITIONS

For Image quality improvements some important concepts get used which are defined below:
PSNR: The distortions present in the stego image are calculated using Peak to Signal Noise
Ratio (PSNR).
MSEcolor: Mean Square Error between the original cover color image and the stego color
image. Formal foundation of secret sharing was formulated using the information theory.
Two important concepts were defined based on information rate: ideal and perfect schemes.
Information Rate: The information rate was studied by Stinson. It is a measure of the
amount of information that the participants need to keep secret in a secret sharing scheme.
The information rate for a particular shareholder is the bit-size ratio (size of the shared secret)
/ (size of that user’s share). The information rate for a secret sharing scheme itself is the
minimum such rate over all participants. The efficiency of a secret sharing scheme is
measured by its information rate.
Ideal Secret Sharing: Secret sharing schemes with information rate 1 are called ideal.
Scheme is ideal if share has the same length as secret. Ideal property can be thought as
efficiency.
Perfect: A perfect threshold scheme is a threshold scheme in which knowing only (t - 1) or
fewer shares reveal no information about Secret S whatsoever, in the information theoretic
sense.

III. REVIEW

3.1 Review of Lin and Tsai's scheme [6]

        Lin and Tsai suggested a secret sharing method which divides a secret image into the
shadows based on t-1 polynomial. These shadows are embedded within a cover image to hide
the secret. [6] added authentication along with steganography to prevent participants from
false stego image changed in active attacks. However the secret image reconstructed using
the above secret sharing method will have distortions because of truncations of gray pixels
values that are greater than 250.
Drawback: Some applications not tolerate even small distortions. Dishonest participants can
easily manipulate the stego image for successful authentication but cannot recover the secret
image. The other shortcoming is that the visual quality of the stego images is not good
enough.



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International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 2, March – April (2013), © IAEME

3.2 Review of chang’s scheme [7]

        Chin-Chen Chang, Yi-Pei Hsieh, Chia-Hsuan Lin overcame drawbacks in Lin an
Tsai’s scheme and proposed a novel secret image sharing scheme combining Steganography
and authentication based on Chinese remainder theorem (CRT). The proposed scheme not
only improves the authentication ability but also enhances the visual quality of the stego
images.

3.3 Review of Yang et al.'s scheme [8]

        Yang, C.N., Chen, T.S., Yu, K.H., Wang, C.C. presented a scheme to improve
authentication ability that prevents dishonest participants from cheating.
The scheme also defines the arrangement of embedded bits to improve the quality of stego-
image. Furthermore, by means of the Galois Field GF(28), they improved the scheme to a
lossless version without additional pixels.

3.4 Review of L.Jani Anbarasi’s scheme [9]

        L.Jani Anbarasi and S.Kannan proposed Novel image secret sharing for color image
which possesses reversible characteristics. Authorized participants are allowed to reconstruct
the secret and the original cover from the stego using the reversibility scheme. This reversible
scheme can be used for medical image processing, artistic images and military images where
the secret is retrieved without any distortion.

IV. COMPARATIVE RESULTS

   The experimental results are produced to compare Lin, Yang, Chang and Anbarasai.

 TABLE 1. Comparison of PSNR for stego image Leena for Lin, Yang, Chang and Anbarasai
                                       schemes
   Cover Image       Secret
                     Share         Lin [8]            Yang [12]    Chang [14]   Anbarasi[20]
                     Image

                                PSNR    DHC      PSNR       DH    PSNR    DHC   PSNR    DHC
                                         %                  C%             %             %



  Brain.bmp          Lenna1     38.85    12.5     41.23      14   37.65    16   41.88    52
  128X128


  Baboon.bmp         Leena2     38.15    12.8     40.43      15   38.65    16   42.88    52
  512X512


PSNR: Peak to Signal Noise Ratio
DHC: Data Hiding capacity


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V. CONCLUSION

        In this paper we have tried to analyze secure secret sharing schemes based on secret
sharing with steganography. These secure secret sharing schemes draw our attention, and we
are also eager to know their specific implementation methods. Also the performances of
existing secure secret sharing schemes are evaluated on Peak Signal to Noise Ratio and Data
Hiding Capacity.

REFERENCES

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