Image Steganography

Hushen Savani (24)Vikas Kantiya (10)

MCA-V

Department of Computer ScienceDepartment of Computer ScienceRollwala Computer CenterRollwala Computer CenterGujarat UniversityGujarat UniversityAhmedabadAhmedabad

Guided by, Guided by, Dr. Jyoti PareekDr. Jyoti Pareek

What is Steganography?

Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message.

• SteganographySteganography• FrameworkFramework• CategoriesCategories• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit

• StatisticsStatistics• OPAPOPAP• Inverted PatternInverted Pattern

• MSE basedMSE based• Entropy basedEntropy based

• PVDPVD• StatisticsStatistics

Steganography Framework• SteganographySteganography• FrameworkFramework• CategoriesCategories• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Categories of Steganography• SteganographySteganography• FrameworkFramework• CategoriesCategories• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




What is Image Steganography?• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Image Steganography is the technique of hiding the data within the image in such a way that prevents the unintended user from the detection of the hidden messages or data.

For example,

Cover Image Data / Message Stego Image

Applications of Image SteganographySecure Private Files and

Documents.Hide Passwords and Encryption

Keys.Transport Highly Private

Documents between International Governments.

Transmit message/data without revealing the existence of available message.

• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Image DomainWhat Images are made up of?:-What Images are made up of?:-

Images are made up of lots of little dots called pixels. Each pixel is represented as 3 bytes 3 bytes – one for RedRed, one for GreenGreen and one for BlueBlue.

Each byte is interpreted as an integer integer numbernumber, which is how much of that color is used to make the final color of the pixel.

11111000 11001001 00000011

248 201 3

248 + 201 + 3 = Orange Color





Image DomainThe difference between two colors

that differ by one bit in either one red, green or blue value is impossible detect for a human eyehuman eye.

So we can change the least significant (last) bit in a byte, we either add or subtract one or more values from the value it represents.

This means we can overwrite the last bit in a byte without affecting the colors it appears to be.





Image DomainA common approach of

hiding data within an image file is Least Significant Bit Least Significant Bit (LSB) Substitution(LSB) Substitution.

In this method, we can take the binary representation of the hidden data and overwrite the LSB of each byte within the cover image.





Least Significant Bit SubstitutionSuppose we have the following binary representation for the Cover Image.

10010101 00001101

10010110 00001111

Suppose we want to "hide" the following 4 bits of data: 10111011,we get the following,

100101011 000011011

100101100 000011111

Where the each data bits are accommodated in the least significant bits of each byte of the image.





Least Significant Bit SubstitutionLeast Significant Bit

Substitution results in a very minor distortion of the image which is very much negligible for the human eyes.

Cover Image Stego Image





Substitution Levels

4-bits 5-bits

6-bits 7-bits





Pixel IndicatorThis method uses the least

two significant bits of one of one of the channelsthe channels to indicate existence of data in the other other two channelstwo channels.





Pixel IndicatorExample,

Initial Pixel Bytes: 10101101 11011010 11100101

Data to be Embedded: 11011101

Channel R: 1010111111

Channel G: 1101100101

Channel B: 1110011111





Pixel Indicator Bits

RR GG BB

Indicating Channel

Channels inwhich Data isEmbedded

Stego Color Cycle

The SCC technique uses the RGB images to hide the data in different channels.

It keeps cycling the hidden data between the Red, Green and Blue channels, utilizing one channel at a cycle time.





Triple-ATriple-A technique uses the same

principle of LSB, where the secret is hidden in the least significant bits of the pixels, with more randomizationrandomization in selection of the number of bits used and the color channels that are used.

•Two Seeds:

•To determine the used channels

•To determine the number of bits used

This randomization is expected to increase the security of the system.





Max-bitThis method measures the

intensityintensity of the pixel and then hides data by random pixel random pixel selection selection with a goal to hide maximum data in each pixel.

This method is divided into three parts:EncryptionImage Intensity CalculationSteganography.





Max-bit• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Original Image

Max-bit• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Grayscale Image Intense Pixels*

* All Black colored pixels are considered as Intense pixels.

Triple-A SCC Max-bit

Bits/pixel 3.428 3 6.281

Capacity Ratio

3.43/24 => 14.28%

3/24 => 12.5%

6.28/24 => 26.1%

Statistics• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Optimal Pixel adjustment Procedure (OPAP) reduces the distortion caused by the LSB substitution method.

In OPAP method the pixel value is adjusted after the hiding of the secret data.

This done to improve the quality of the stego image without disturbing the data hidden.

Optimum Pixel Adjustment Procedure • SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




First a few least significant bits are substituted with the data to be hidden.

Then in the pixel, the bits before the hidden bits are adjusted suitably if necessary to give less error.

Let nn LSBs be substituted in each pixel.

Let dd= decimal value of the pixel after the substitution.

d1d1 = decimal value of last n bits of the pixel.

d2d2 = decimal value of n bits hidden in that pixel.





If(d1~d2)<=(2^n)/2then no adjustment is made

in that pixel.Else

If(d1<d2)d = d – 2^n .

If(d1>d2)d = d + 2^n .

Where,d is converted to binary and

written back to pixel





Retrieval Process of DataRetrieval Process of Data:The retrieval follows the extraction of the least significant bits(LSB) as hiding is done using simple LSB substitution.





This inverted pattern (IP) LSB substitution approach uses the idea of processing secret messages prior to embedding.

In this method each section of secret images is determined to be inverted or not inverted before it is embedded.

In addition, the bits which are used to record the transformation are treated as secret keys or extra data to be re-embedded.

Inverted Pattern• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




The embedded string is S, the replaced string is R, and the embedded bit string to divided to P parts.

Let us consider n-bit LSB substitution to be made. Then S and R are of n-bits length.

For P part in i = 1 to P If MSE(Si,Ri) ≤ MSE(S’i,Ri)

Choose Si for embedding Mark key(i) as logic ‘0’

If MSE(Si,Ri) ≥ MSE( S‘i,Ri) Choose S‘ i for embedding Mark key(i) as logic ‘1’

End For

Where, MSE = Mean Squared ErrorS is the data to be hidden S‘ is the data to be hidden in inverted form.





Retrieval Process of DataRetrieval Process of Data:The stego-image and the key file

are required at the retrieval side. First corresponding numbers of

LSB bits are retrieved from the stego-image.

If the key is ‘0’, then the retrieved bits are kept as such.

Else if the key is ‘1’, then the bits are inverted.

The bits retrieved in this manner from every pixel of the stego-image gives the data hidden.





Relative entropy measures the information discrepancy between two different sources with an optimal threshold obtained by minimizing relative entropy.

In this method, instead of finding the mean square error for inverted pattern approach, the relative entropy is calculated to decide whether S or S‘ suites the pixel.

IP Method Using Relative Entropy• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Divide the cover image into P blocks of same size, the embedding string is S, and the replaced string is R.

For P part in i =1 to P

If rel.entropy(Si,Ri) ≤ rel.entropy (S‘i,Ri)

Choose Si for embedding

Mark key(i) as logic ‘0’

If rel.entropy (Si,Ri) ≥ rel.entropy (S‘i,Ri)

Choose S‘i for embedding

Mark key(i) as logic ‘1’

End For

Where,S is the data to be hiddenS‘ is the data to be hidden in inverted form.

IP Method Using Relative Entropy• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Peak Signal to Noise Ratio (PSNR):-Peak Signal to Noise Ratio (PSNR):- The PSNR is calculated using the

equation,

where Imax is the intensity value of each pixel which is equal to 255 for 8 bit gray scale images.

Mean Square Error (MSE):-Mean Square Error (MSE):- The MSE is calculated using the equation,

where M and N denote the total number of pixels in the horizontal and the vertical dimensions of the image Xi, j represents the pixels in the original image and Yi, j, represents the pixels of the stego image.

Decision Factors• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Pixel Value Differencing (PVD) is able to provide a high quality stego image in spite of the high capacity of the concealed information.

That is, the number of insertion bits is dependent on whether the pixel is an edge area or smooth area.

In edge area the difference between the adjacent pixels is more, whereas in smooth area it is less.

Pixel Value Differencing• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit







• PVDPVD• StatisticsStatistics • While human perception is less sensitive to

subtle changes in edge areas of a pixel, it is more sensitive to changes in the smooth areas.

Smooth Area

Edge Area

This method hides the data in the target pixel by finding the characteristics of four pixels surrounding it, indicated in the table below:





Select the maximum and the minimum values(g) among the three pixel values that have already finished the embedding process.

Consider upper pixel (g1), left pixel (g2) and the upper left pixel (g3) in a given target pixel g(x,y)

Calculate d using following: d= [max (g1, g2, g3) – min (g1, g2,

g3)] Using d , we get an idea as to

whether the target pixel is included in an edge area or in smooth area.





Calculation of n: the number of the insertion bits in a target pixel Px,y is calculated, using the following formula:





OPAP IP PVD

Size of secret data

Image Size

25 kb

242 kb

24.5 kb

242 kb

22 kb

242kb

MSE 0.1503 0.2635 12.4715

PSNR 56.71 51.86 37.87

Time (s) 7.65 7.96 8.6

Statistics• SteganographySteganography• CategoriesCategories• FrameworkFramework• Image SteganographyImage Steganography• ApplicationsApplications• Image DomainImage Domain• -- Methods ---- Methods --• LSB LSB • PIPI• SCCSCC• Triple-ATriple-A• Max-bitMax-bit




Image Steganography

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