=Paper= {{Paper |id=Vol-1490/paper33 |storemode=property |title=Computer-aided system of data protection by steganographymethods |pdfUrl=https://ceur-ws.org/Vol-1490/paper33.pdf |volume=Vol-1490 }} ==Computer-aided system of data protection by steganographymethods== https://ceur-ws.org/Vol-1490/paper33.pdf
Image Processing and Geoinformatics



          Computer-aided system of data protection by
                   steganography methods

                                Kiseleva A.V., Kudrina М.A.

                               Samara State Aerospace University



        Abstract. The article contains the description of the computer-aided system
        which allows to hide information by means of steganography methods. The
        system involves methods of hiding text information such as LSB, Koch-Zhao
        method, and method of Kutter-Jordan-Bossen, as well as the method of hiding
        color bmp images.

        Keywords: steganography methods, data hiding, information security, data
        protection


        Citation: Kiseleva A.V., Kudrina М.A. Computer-aided system of data
        protection by steganography methods. Proceedings of Information Technology
        and Nanotechnology (ITNT-2015), CEUR Workshop Proceedings, 2015; 1490:
        277-284. DOI: 10.18287/1613-0073-2015-1490-277-284


1. Introduction
   Modern society faces an up-to-date problem concerning the means which help to
protect confidential information when it is stored or sent. The steganography is one of
ways of data protection.
   Steganography involves hiding message in such a way that the casual observer
would not be able to detect the hidden information.
   Due to the increase of global computer networks role, the value of steganography
becomes more and more important. Now steganography systems are actively used for
the solution of the following main tasks [1]:

 protecting confidential information against unauthorized access;
 overcoming the monitoring and management systems of network resources;
 camouflaging the software;
 copyright protection of some types of intellectual property.


2. Theoretical part
   The steganography system is a set of means and methods which are used for
formation of the hidden channel of information transfer [2, 3]. The embedded-
message or payload is something to be hidden in something else. Any type of
information can be used as the embedded-message: texts, images, videos, etc.


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   The carrier or the cover message is the signal, stream, or data file that hides the
embedded-message. The resulting signal, stream, or data file with the encoded
payload is called the package or stego-file.
   Computer steganography methods can be divided into two basic classes in
accordance with the hiding principle: methods of direct replacement and spectral
methods. Methods of direct replacement use redundancy of data environment and
consist in the replacement of insignificant part of the cover message with bits of the
embedded-message. Spectral methods of data hiding use spectral representations of
the environment elements with the embedded-message within the environment
structure.
   LSB method
   The method of replacement of Least Significant Bits (LSB method) is the most
common nowadays. The method consists in replacing final bits in cover message
bytes with bits of the embedded-message. The difference between empty and filled
cover message has to be imperceptible for the human perception system [4]. The
scheme of LSB method is shown in figure 1.
   Method of Kutter-Jordan-Bossen
   This method is based on the peculiarity of human visual system, which consists in
low susceptibility of a human to changes in brightness of blue color in comparison
with red and green colors.




                              Fig. 1. – The scheme of LSB method




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      One bit of the embedded-message is written to one pixel of the cover message.
The brightness of red and green components of pixel remains unchanged, but the
brightness of blue component changes in accordance with the following formula [5]:
            Bx , y  Yx , y, if mi  1,
B x*, y                                                                          (1)
            Bx , y  Yx , y, if mi  0,
where 𝐵𝑥,𝑦 – the brightness of blue component of the pixel with coordinates (x,y);
      Bx*, y – the changed brightness of blue component of the pixel with coordinates
(x,y);
   Yx,y = 0.29890Rx,y+0.58662Gx,y+0.11448Bx,y – pixel brightness;
   Rx,y – the brightness of red component of the pixel with coordinates (x,y);
   Gx,y – the brightness of green component of the pixel with coordinates (x,y);
   mi – i-bit of the embedded-message;
   λ = 0.1 – the coefficient setting the energy of the built-in bit of data (it is set
depending on the functional purpose and features of steganography system). When λ
increases, the embedded-message becomes more apparent, but it is more resistant to
distortions.
   Since the recipient doesn’t have the original image, it is impossible to find out
whether the brightness of blue component increased or decreased. Therefore, in order
to extract the information, brightness of blue component should be predicted [6]:
          

          (B    x, y  i    Bx , y  i  Bx  i , y  Bx  i , y )
Bx , y  i1                                                           ,                                         (2)
                                     4

where σ = 1÷3 – the size of the area on which brightness will be predicted.
  The following formula is used for extracting the embedded-message:

            
     1, if Bx , y  B x , y ,
mi          
     0, if Bx , y  B x , y .
     

    Koch-Zhao method
    Koch-Zhao method uses frequency characteristics of the cover message and
consists in relative replacement of the discrete cosine transformation (DCT)
coefficients. The image is divided into blocks with dimension 8×8 pixels and DCT is
applied to each block. Each block is suitable for recording one information bit [7].
This method has high resistance to image distortion, even to its significant change, but
it can’t be used for hiding large volumes of data.
    Hidden transmission of color images
    24-bit bitmap-pictures are used as input images; each color contains 8 bits of
information. The data are hidden by using LSB method. The essence of the algorithm
is that the secret image is divided into three color primitives (tints of red, green and
blue), and then each primitive is put into the least significant bits of one of image
containers. Thus, after the data is hidden, each cover message will contain only one
color component of the secret image [8-10].

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   Two most significant bits from each color primitive of the secret image are
recorded to the least significant bits of the corresponding color of the corresponding
carrier. In figure 2 you can see the illustration of the method of image hiding. Two
least significant bits of other colors are nulled. This operation is repeated for each
pixel.
   To restore the secret image, you need to take the first pixel from each carrier. Two
least significant bits of each color component of this pixel are becoming the most
significant bits and corresponding color components are added. This operation is
repeated for each pixel and secret image is restored.




                       Fig. 2. – Illustration of the method of image hiding


3. Realization of the system
   The researched carried out within the frame of bachelor’s final qualifying work
initiated the development of computer-aided system of data protection, which hides
information using steganography methods. This system allows you to select a
container for embedding information, to choose an embedding method, to create a
stego-file and to extract secret information from the stego-file.
   The system performs the following functions:

 embedding text information;
 embedding an image;
 extracting text information;
 extracting an image.


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   After the system starts, the window for embedding messages opens and the user
can click "Load Container" in the menu and select a file to download. The selected
image will be displayed on the screen. After that the user has to choose an embedding
method, for example, LSB, and click on "Write" button to enter the secret message.
After embedding, the user can save the filled cover message. For extraction of the
embedded message, it is necessary to pass to "Read the message" tab. Click on
"Read" button, select the file, and the secret message appears in the text field.
   To hide an image, the user needs to go to the tab "Hide the picture" (see figure 3),
to load three containers and the secret image. All images will be displayed in the
form. The user needs to select the number of replaceable bits. It influences the quality
of the stego-file and the extracted message.




                  Fig. 3. – Embedding the image using 1 bit of container color

    Select the number of replaceable bits which equals 1, press "Save" button and save
all of the containers.
    To restore the image, it is necessary to pass to tab «Restore image», to load
containers and to press «Restore» button.


4. Experimental part
   The carried out research demonstrated how the number of replaced bits in RGB
components of the container pixels influences the quality of the restored image and
container distortion.
   Figures 4 - 6 illustrate results of LSB-algorithm with 1, 4 and 8 replaced bits.
   It’s clear that 1 bit replacement distorts the secret image considerably, but the
change of the containers is invisible. When 4 bits are replaced, the secret message is
distorted slightly, but embedding can be noticed in the containers. When 8 bits are
replaced, the secret image can not be transmitted unnoticed because containers are
RGB components of the secret image. Furthermore, when the amount of replaced bits


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is the same (e.g., 4), the distortion can be seen better in the light container than in the
dark one.




                        Fig. 4. – Restoring the image with 1 replaced bit




                        Fig. 5. – Restoring the image with 4 replaced bits




                        Fig. 6. – Restoring the image with 8 replaced bits



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   Figures 7-8 are dependency graphs which illustrate the relation between mean-
square-error of RGB container distortion and the number of replaced bits in
containers, presented for the dark and the light image containers respectively.

                160

                140

                120

                100
                                                                                                    red
          MSE




                 80                                                                                 green
                                                                                                    blue
                 60

                 40

                 20

                   0
                       0              2          4               6            8          10
                                              nubmer of changed bits



Fig. 7. – Dependency graphs of MSE distortion and the quantity of changed bits for the dark
container


               250


               200


               150                                                                                          red
         MSE




                                                                                                            green
               100                                                                                          blue


                50


                 0
                       0              2              4               6            8           10
                                              nubmer of changed bits


Fig. 8. – Dependency graphs of MSE distortion and the quantity of changed bits for the light
container

   Mean-square-error (MSE) is calculated using the following formula:
                 n m
                  ( xi , j  xi , j )
                                  *       2

                i 1 j 1
   MSE                      ,                                                                             (3)
                  mn
where n – the length of the image;
  m – the width of the image;


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   xi , j – the value of pixel color component of the original image;
   xi*, j – the value of pixel color component of the modified image.
   The graphs show that the increase in the number of changed bits leads to MSE
increase. In addition, it is evident that mean-square-error for the light image is larger
than for the dark one.
   Thus, it can be concluded that darker images serve better in the function of
containers and the number of bits should be restricted to 3-4. Following these
recommendations will help to achieve the best balance between the quality of the
transmitted image and the degree of distortion of containers.


5. Conclusion
   The researched carried out within the frame of bachelor’s final qualifying work
implied the study of steganography methods and the development of computer-aided
system of data protection by means of the following steganography methods: LSB
method, Koch-Zhao method, Kutter-Jordan-Bossen method and the method of color
bmp images hiding.


References
 1. Steganography yesterday, today and tomorrow. Source: . [in Russian]
 2. Basic principles of steganography. Source: . [in Russian]
 3. Pfitzmann B. Information hiding terminology. Lecture Notes in Computer Science, 1996;
    1174: 347-350.
 4. Replacement          of     the    least   significant    bit,    or   LSB.       Source:
    . [in Russian]
 5. Modification of Kutter-Jordan- Bossen method of information hiding. Source: . [in Russian]
 6. Kutter-Jordan-Bossen method of steganography. Source: . [in Russian]
 7. Koch-Zhao method of steganography. Source: . [in
    Russian]
 8. Visual cryptography for color images. Source: . [in
    Russian]
 9. Dryuchenko MA, Sirota AA. Steganography algorithm for information hiding based on
    spatial deformation of full-color image fragments. Computer Optics, 2014; 38(4): 833-842.
    [in Russian]
10. Glumov N, Mitekin V. A new semi-fragile watermarking algorithm for image
    authentication and information hiding. Computer Optics, 2011; 35(2): 262-267. [in
    Russian]




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