The document describes a steganography application that uses a genetic shifting algorithm to securely hide messages in digital images. It begins with definitions of steganography and discusses its history and various techniques. It then describes implementing a genetic shifting algorithm to securely hide information in images by shifting pixel values, making the hidden data harder to detect through statistical analysis. The document outlines testing the application, including comparing results with and without the genetic shifting algorithm across different message lengths and images. In summary, the document proposes and tests a genetic shifting algorithm for secure steganography by hiding messages in digital images in a way that is difficult to detect through statistical analysis.
1. Steganography application of effective
Genetic Shifting Algorithm against RS
Analysis
Advisor: MScEE, Vladislav Kaplan
Vadim Purinson LV Tailoring Software
2. 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
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3. 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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4. 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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5. 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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7. 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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8. Digital image definition
A 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
9. 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
10. 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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11. IMAGE STEGANOGRAPHY TECHNIQUES
Least Significant Bit insertion LSB
Masking and filtering
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16. The properties of the human eye
used in the steganography .
selectivity to brightness fluctuations;
frequency sensitivity;
masking effect;
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17. 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.
21. 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.
23. 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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28. Genetic Shifting Algorithm (Shen Wang )
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Before or After ?
=
+ 1
1
this is number of pixels, and ( + 1) and
are indicate current and next pixel values.
30. Front Panel
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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
Communica
tions
Sound &
Vibration
Vision
Controls palette view
37. 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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38. Compare visual image degradation
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LSB-1
The recovered text file size is 6.21 KB
(6,361 bytes), 1177 words text,
equivalent to 2.5 pages in WORD
format.
40. Compare visual image degradation
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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.
41. 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.
42. Compare visual image degradation
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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 225 225 ヰ image by
using 4LSB plane.
44. 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.
45. Compare visual degradation through
common tools
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Histogram degradation trough of
message enlargement for 4LSB level