Project presentation - Steganographic Application of improved Genetic Shifting algorithm against RS analysis - BScEE final assignment by Vadim Purinson, adviser Vladislav Kaplan MScEE

Steganography application of effective Genetic Shifting Algorithm against RS

Analysis

Advisor: MScEE, Vladislav Kaplan

Vadim Purinson LV Tailoring Software

Who owns the information – owns the world

Rotschild Nathan Mayer•What is Steganography?

•Why Steganography?•History of Steganography.•Digital steganography.•Steganalysis.•RS Fridrich analysis.•Genetic shifting algorithm.•Software implementation. •Tests•Conclusions

04/15/2023LV Tailoring Software

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What is Steganography?

The art and science of hiding information by embedding it in some other media.

•Steganography versus cryptography

•In general, steganography approaches hide a message in a cover e.g. text, image, audio file, etc.


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Why Steganography?

•Transfer secret information or embed secret messages into media.

•Data, intellectual property and privacy protection - Digital Water marking, medical data.


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History of Steganography.•400 B.C. – writings of Herodotus•1499 – “Steganographia”, Trithemius –

steganography and magic.•1665 – Steganographica, Gaspari Schotti.•1870 – The Pigeon Post into Paris.

Most popular example in history this is use invisible inks.


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Terminology and Definitions•


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Equation 3

Equation 4

Terminology and Definitions

•Steganographic system or stegasystem – this is set of tools and methods are used to generate a secret channel of information transmission.


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Digital image definitionA digital image is binary representation of a two dimensional image and contains a fixed number of rows and columns of pixels.

• Pixel• Byte• Bit


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Equation 1

Message embedding mathematical definition

8 bit Grayscale equivalents to 1 byte per pixel. For example, for the image size of 7 Kbyte maximum message size can be embedded, by using 1 LSB is 7168 bit


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Equation 2

Digital steganography.Advantages of digital images

steganography is:

• There are a variety of methods used in which information can be hidden in the images.

• Relatively large volume of digital images representation, that allows the embedding of large amount of information.

• Known size of the cover media, that absence of restrictions, requirements imposed by real-time.

• Presence of relatively large textural regions in most digital images that have noise structure and well suited for information integration.

• Weak sensitivity of the human eye to minor changes the color of the image, brightness, contrast and the noise presence.

• Image steganography has come quite far with the development of fast, powerful graphical computers.


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IMAGE STEGANOGRAPHY TECHNIQUES

•Least Significant Bit insertion – LSB

•Masking and filtering


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The simple LSB schema


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LSB - Example


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Lena Söderberg

LSB - Example

“A” = 65(decimal) = 10000001 (binary)


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Classification of Steganography Methods.

•Substitution methods in spatial domain = LSB;

•Transform domain = frequency domain;•Spread spectrum techniques;•Statistical methods;•Distortion techniques; •Cover generation methods;


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The properties of the human eye used in the steganography

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•selectivity to brightness fluctuations;

•frequency sensitivity;

•masking effect;


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Selectivity to brightness fluctuations


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Human eye sensitivity to contrast.

Experimental data by Aubert (1865), Koenig and Brodhun (1889) and Blanchard (1918). It indicates that the Weber-Fechner law - according to which the smallest perceptible change in intensity vs. intensity level I is constant.

Frequency sensitivity


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Sensitivity of eye for the colors

Masking effect 04/15/2023LV Tailoring Software

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Herman Grid

Steganalysis

•Steganalysis

•Steganalyst

•Attack on steganography system


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Stegattacks classes• Attack with the knowledge of the modified media

only. • Attack with knowledge of unmodified container.


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The results of stegattack

• Detect secret message presence.• Recover secret message from stegoimage.• Destroy the message in case no possibility to

recover message.

Steganalysis hierarchy


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Main methods of stegattack

•Visual analysis – detect visual image degradation by “naked” eye.

•Statistical Histogram and STD analysis.

•Detection methods are based on data hiding analyzing the characteristics of the probability distribution of the container.


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Visual Attacks


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Grayscale image visual attack example

Grayscale image filter visual attack example

Histogram Analysis Attack


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Statistical Analysis Attack

•Stego Only Attack;

•Known Cover Attack;

•Known Message Attack;

•Blind Steganalysis;

•Semi-blind;


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Fridrich RS Analysis

•“regular”•“singular”•“unchanged”


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←𝑅−𝑚𝑆−𝑚→𝑅𝑚↔𝑆𝑚𝑅𝑚>𝑆𝑚

𝑅−𝑚>𝑆−𝑚

Genetic Shifting Algorithm (Shen Wang )


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Before or After ?

𝐶=∑𝑖

𝑁 (𝑖+1 )− 𝑖𝑁−1

– this is number of pixels, and and are indicate current and next pixel values.

Vadim Purinson

Introduction to LabVIEW


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Front Panel04/15/2023LV Tailoring Software

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Example of Front panel view

• Modern• System• Classic• Express• Control

Design & Simulation

• .Net & ActiveX

• Signal processing

• Add ons• User

Controls• Select and

control• DSC

Module• RF

Communications

• Sound & Vibration

• VisionControls palette view

Block diagram


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Function palette Example of Block diagram view

More functions

•Tools palette • Operating tool• Positioning tool• Labeling tool• Wiring tool


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• Wiring

• SubVis

Basic LabVIEW Hierarchy04/15/2023LV Tailoring Software

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Front panel view04/15/2023LV Tailoring Software

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1. Source cover image

2. Result stegoimage

3. Cover Histogram and STD statistic window

4. Stegoimage Histogram and STD statistic window

5. RS analysis results on Stegoimage

6. LSB level to be used (up to LSB-4)

7. Start shifting (GSM)

8. Standard deviation evaluation

9. Snaked array length.

10. Open output result text message

11. Decode message from stegoimage

12. Encode message into cover message

13. Stop button

14. Start / stop menu

Steganography directory view


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Encoding Decoding Example04/15/2023LV Tailoring Software

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Steps definition

• Perform basic message coding (Cover Image) up to LSB-4 for gray images.

• Perform basic message recovery (Stego Image) up to LSB-4 for gray images.

• Compare visual image degradation.• Compare visual degradation through common tools (Histogram,

STD). • Perform study of coded message saturation (message of different

length) vs. recovery and image degradation per different LSB coding at gray images.

• Build RS analysis (Fridrich algorithm) routine.• Confirm validity of RS analysis on gray images.• Implement secure genetic steganography method for RS baseline

shifting for LSB-1. (GSM for RS shifting).• Perform basic message recovery with GSM for RS shifting for

LSB-1.• Perform RS analysis comparison for different message length

with GSM for RS shifting and without, use different “snake” division array image representation.


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Compare visual image degradation


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LSB-1The recovered text file size is 6.21 KB (6,361 bytes), 1177 words text, equivalent to 2.5 pages in WORD format.

Compare tool04/15/2023LV Tailoring Software

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Compare visual image degradation04/15/2023LV Tailoring Software

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LSB-2

The recovered text file size is 12.4 KB (12,737 bytes), 2228 words text, equivalent to 5 pages in WORD format.

Compare visual image degradation


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LSB-3

The recovered text file size is 18.6 KB (19,106 bytes), 3317 words text, equivalent to 7.5 pages in WORD format.

Compare visual image degradation04/15/2023LV Tailoring Software

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LSB-4

The recovered text file size is 24.8 KB (25,477 bytes), 4468 words text, equivalent to 10 pages in WORD format – this is a maximum text file size can be imbedded into image by using 4LSB plane.

Compare visual degradation through common tools


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Different depth of the LSB

Blue line is displays Cover image Histogram and red line represents manipulated image distribution.



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Histogram degradation trough of message enlargement for 4LSB level



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STD view

Build RS analysis (Fridrich algorithm) routine.


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Build RS analysis (Fridrich algorithm) routine


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LSB-1

differences versus message volume.


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Image1

Message % of Rm % of Sm diff

Message

length(bytes) % of image

0 54.9 45.1 9.8 0 0

1 53.8 46.2 7.6 699 1.05

2 52.1 47.9 4.2 2,225 3.35

3 51.5 48.5 3 4,055 6.11

4 51.4 48.6 2.8 4,222 6.36

5 50.8 49.2 1.6 6,201 9.34

6 49.8 50.2 -0.4 8,169 12.3

Image2

0 54.2 45.8 8.4 0 0

1 53.9 46.1 7.8 699 1.78

2 52.5 47.5 5 2,225 5.67

3 51.8 48.2 3.6 4,055 10.34

4 51.7 48.3 3.4 4,222 10.76

5 50 50 0 6,201 15.8

6 49.8 50.2 -0.4 6,361 16.33

Image3

0 52.5 47.5 6 0 0

1 52 48 5 699 1.05

2 51.8 48.2 4.4 2,225 3.35

3 51.9 48.1 4 4,055 6.11

4 51.7 48.3 4 4,222 6.36

5 50.9 49.1 3.4 6,201 9.34

6 50.8 49.2 0.6 8,169 12.31

Build RS analysis (Fridrich algorithm) routine


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Image 2 RS analysis results.


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2LSB

Message

% of

Rm % of Sm diff

Message

length(bytes)% of

image

0 54.2 45.8 8.4 0 0

1 54 46 8 699 1.78

2 53.4 46.6 6.8 2,225 5.67

3 52.8 47.2 5.6 4,055 10.34

4 52.7 47.3 5.4 4,222 10.76

5 52.1 47.9 4.2 6,201 15.8

6 50.9 49.1 1.8 12,737 24.31

3LSB

0 54.2 45.8 8.4 0 0

1 54.2 45.8 8.4 699 1.78

2 54.2 45.8 8.4 2,225 5.67

3 53.9 46.1 7.8 4,055 10.34

4 53.9 46.1 7.8 4,222 10.76

5 53.4 46.6 6.8 6,201 15.8

6 52 48 4 19,106 36.47

4LSB

0 54.2 45.8 8.4 0 0

1 54.1 45.9 8.2 699 1.78

2 54 46 8 2,225 5.67

3 53.9 46.1 7.8 4,055 10.34

4 53.9 46.1 7.8 4,222 10.76

5 53.4 46.6 6.8 6,201 15.8

6 50.3 49.7 0.6 25,477 48.56

Build RS analysis (Fridrich algorithm) routine (30 images )


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Secure genetic steganography method


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13 and 29 division snaked array LSB-1 RS analysis results


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Image 1

Message % of Rm

% of

Sm diff

Message

length(bytes)% of imager

0 63 37 26 0 0

1 60.9 39.1 21.8699 1.33

2 56.9 43.1 13.82,225 4.24

3 54.5 45.5 9 4,055 7.74

4 54.5 45.5 9 4,222 8.06

5 52.4 47.6 4.8 6,201 11.83

6 51.1 48.9 2.2 6,361 12.14

Image 2

0 60 40 20 0 0

1 58.9 41.1 17.8699 1.05

2 57.1 42.9 14.22,225 3.35

3 55.3 44.7 10.64,055 6.11

4 55.5 44.5 11 4,222 6.36

5 51.7 48.3 3.4 6,201 9.34

6 51.1 48.9 2.2 8,169 12.3

Image3

0 58.1 41.9 16.20 0

1 56.6 43.4 13.2699 1.05

2 55 45 10 2,225 3.35

3 54.2 45.8 8.4 4,055 6.11

4 54.3 45.7 8.6 4,222 6.36

5 53.3 46.7 6.6 6,201 9.34

6 50.9 49.1 1.8 8,169 12.31

Image 1

Message % of Rm % of Sm diff

Message

length(bytes)

% of

image

0 58.7 41.3 17.4 0 0

1 57 43 14 699 1.05

2 54.5 45.5 9 2,225 3.35

3 53 47 6 4,055 6.11

4 52.8 47.2 5.6 4,222 6.36

5 51.2 48.8 2.4 6,201 9.34

6 50.5 49.5 1 8,169 12.3

Image 2

0 56.9 43.1 13.8 0 0

1 56 44 12 699 1.33

2 53.7 46.3 7.4 2,225 4.24

3 52.1 47.9 4.2 4,055 7.74

4 52.1 47.9 4.2 4,222 8.06

5 49.9 50.1 -0.2 6,201 11.83

6 49.7 50.3 -0.6 6,361 12.14

Image3

0 54.9 45.1 9.8 0 0

1 53.8 46.2 7.6 699 1.05

2 52.7 47.3 5.4 2,225 3.35

3 52.6 47.4 5.2 4,055 6.11

4 52.5 47.5 5 4,222 6.36

5 52.1 47.9 4.2 6,201 9.34

6 50.6 49.4 1.2 8,169 12.31

13 division snaked array 29 division snaked array

Secure genetic steganography method


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No shifted 13 division snake array

29 division snake array 51 division snake array

Conclusions


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Thank you for your attention

04/15/2023

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LV Tailoring Software

Project presentation - Steganographic Application of improved Genetic Shifting algorithm against RS analysis - BScEE final assignment by Vadim Purinson, adviser Vladislav Kaplan MScEE

Engineering

digital steganography

history of steganography

image steganography

trithemius steganography

steganography approaches

software implementation

digital image definition

image size