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INDIN04 Berlin, 25 June 04. 2. Motivation. Security, Privacy, Anti-virus, Trusted computing, intrusion detection and information protectionCritical components for industrial based IT solutions Third party vendors for protection IssuesTrust of the third parties one industrial system, may have se
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1. INDIN04 Berlin, 25 June 04 1 Grey Level Modification Steganographyfor Secret Communication V. POTDAR and E. CHANG
M.Adnan KHAN
Curtin University of Technology
Perth Western Australia Image Pixels
Each image is composed of finite elements each of which has a definite location and amplitude. These elements are referred as image pixels.
Grey Scale or Grey Level Values
Grey scale is a calibrated sequence of grey shades ranging from black to white with intermediate shades of grey. It has a finite range [0, 2N-1], N is the number of bits. If the pixels of a grey-scale image have N bits, they may take values from zero, representing black up to 2N-1, representing white with intermediate values representing increasingly light shades of grey. Grey level values of an 8 bit grey scale image range from 0 to 255.
Grey Scale Image
A grey scale image is defined as an image whose pixel values span the grey scale i.e. [0, 2N-1].
Grey Level Modification
Grey level modification is defined as a technique in which the grey level values of the image pixels are modified in accordance with a mathematical function, to represent binary data. Each pixel has a distinct grey level value which can have an odd or even value. This odd or even value of the grey level is appropriately modified to represent binary data.
Grey level modification Steganography
It is a technique to map data (not embed or hide it) by modifying the grey level values of the image pixels. GLM Steganography uses the concept of odd and even numbers to map data within an image. It is a one-to-one mapping between the binary data (i.e. a bit stream with 1s and 0s) and the selected pixels in an image. From a given image a set of pixels are selected based on a mathematical function. The grey level values of those pixels are examined and compared with the bit stream that is to be mapped in the image. Initially, the grey level values of the selected pixels (which are odd) are made even by changing the grey level by one unit. Once all the selected pixels have an even grey level it is compared with the bit stream which has to be mapped. The first bit from the bit stream is compared with the first selected pixel. If the first bit is even (i.e. 0), then the first pixel is not modified as all the selected pixels have an even grey level value. But if the bit is odd (i.e. 1), then the grey level value of the pixel is decremented by one unit to make its value odd, which then would represent an odd bit mapping. This is carried out for all bits in the bit stream and each and every bit is mapped by modifying the grey level values accordingly. Figure 1 gives a diagrammatic view of the technique.Image Pixels
Each image is composed of finite elements each of which has a definite location and amplitude. These elements are referred as image pixels.
Grey Scale or Grey Level Values
Grey scale is a calibrated sequence of grey shades ranging from black to white with intermediate shades of grey. It has a finite range [0, 2N-1], N is the number of bits. If the pixels of a grey-scale image have N bits, they may take values from zero, representing black up to 2N-1, representing white with intermediate values representing increasingly light shades of grey. Grey level values of an 8 bit grey scale image range from 0 to 255.
Grey Scale Image
A grey scale image is defined as an image whose pixel values span the grey scale i.e. [0, 2N-1].
Grey Level Modification
Grey level modification is defined as a technique in which the grey level values of the image pixels are modified in accordance with a mathematical function, to represent binary data. Each pixel has a distinct grey level value which can have an odd or even value. This odd or even value of the grey level is appropriately modified to represent binary data.
Grey level modification Steganography
It is a technique to map data (not embed or hide it) by modifying the grey level values of the image pixels. GLM Steganography uses the concept of odd and even numbers to map data within an image. It is a one-to-one mapping between the binary data (i.e. a bit stream with 1s and 0s) and the selected pixels in an image. From a given image a set of pixels are selected based on a mathematical function. The grey level values of those pixels are examined and compared with the bit stream that is to be mapped in the image. Initially, the grey level values of the selected pixels (which are odd) are made even by changing the grey level by one unit. Once all the selected pixels have an even grey level it is compared with the bit stream which has to be mapped. The first bit from the bit stream is compared with the first selected pixel. If the first bit is even (i.e. 0), then the first pixel is not modified as all the selected pixels have an even grey level value. But if the bit is odd (i.e. 1), then the grey level value of the pixel is decremented by one unit to make its value odd, which then would represent an odd bit mapping. This is carried out for all bits in the bit stream and each and every bit is mapped by modifying the grey level values accordingly. Figure 1 gives a diagrammatic view of the technique.
2. INDIN04 Berlin, 25 June 04 2 Motivation Security, Privacy, Anti-virus, Trusted computing, intrusion detection and information protection
Critical components for industrial based IT solutions
Third party vendors for protection
Issues
Trust of the third parties
one industrial system, may have several trustees
Solutions
Use own security guard
3. INDIN04 Berlin, 25 June 04 3 Proposed Solution Steganography for security and information protection
an information hiding technique
without a need for third party trustees
Secret Communication
4. INDIN04 Berlin, 25 June 04 4 Steganography Methods of transmitting secret messages through Carriers such as images, audio, video, text, or any other digitally represented code.
The hidden message may be plaintext, ciphertext, or any-thing that can be represented as a bit stream.
The problem:
Can be detected by careful statistical analysis
5. INDIN04 Berlin, 25 June 04 5 Challenges the secrecy of the cover medium
the robustness of the algorithm used
To protect secrecy, we need to
- discover new and better cover mediums or
- design and develop robust algorithms
The difficulties
(a) information embedding capacity and
(b) robustness of algorithms against detection
6. INDIN04 Berlin, 25 June 04 6 Existing Research The existing research shows that the best way is to oversee the level of modification that is made to the cover media.
IF modified too much: the statistical changes are evident and such changes can indicate the use of steganography
IF cannot be intelligently modified in a most secret way, it results in less embedding capacity
7. INDIN04 Berlin, 25 June 04 7 Existing Research Existing Steganographic mediums and techniques suffer from a myriad of attacks on images, video and audio [Johnson and Jajodia ]
Great effort to defend the attacks by improving cover medium OR communication protocols.
Defending techniques through covered medium
Defending techniques through protocols
8. INDIN04 Berlin, 25 June 04 8 Existing Research Defending techniques through covered medium
Replacing Least Significant Bit [Chen 2001, Lee et al. 2000]
Replacing Moderate Significant Bit [Chan and Chang 2001 ]
Pixel Modification Techniques [ Zincheng et al. 2003, Wu et al. 2003, Xinpeng and Shuozhong, 2003, Soo-Chang and Jing-Ming, 2003 Zincheng et al. 2003] etc.
Defending techniques through protocols
the weaknesses of the TCP/IP [ Fisk et al. 2002 ]
email headers [ Bao et al. 2002 ]
the discrete cosine transform (DCT) and the discrete wavelet transform (DWT) [Chang et al. 2002, and Hsu et al. 1999].
9. INDIN04 Berlin, 25 June 04 9 Existing Research this scheme is sensitive to a variety of image processing attacks like compression, cropping
it degrades the quality of stego-image
trade off high embedding rate
vulnerable to steganalysis- based on histogram of pixel value differences
10. INDIN04 Berlin, 25 June 04 10 A New Steganographic Approach embeds data or information within the spatial domain of the greyscale images by modifying the grey level values of the pixels.
11. INDIN04 Berlin, 25 June 04 11 Preliminary Concepts A digital image f(x, y), When the values x, y and f are finite values then we call such an image a digital image.
A image pixel is a definite location and amplitude that compose a image.
Grey scale is Grey Level Values, a sequence of grey shades from black to white with intermediate shades of grey. It has a finite range [0, 2N-1],
an 8 bit grey scale image range is from 0 to 255.
12. INDIN04 Berlin, 25 June 04 12 Preliminary Concepts Grey Level Modification is defined as a technique in which the grey level values of the image pixels are modified in accordance with a mathematical function, to represent binary data. Each pixel has a distinct grey level value which can have an odd or even value. This odd or even value of the grey level is appropriately modified to represent binary data.
13. INDIN04 Berlin, 25 June 04 13 Grey Level Modification Steganography (GLMS)
GLMS is a technique in which the grey level values of the image pixels are modified in accordance with a mathematical function, to represent binary data.
Each pixel has a distinct grey level value which can have an odd or even value. This odd or even value of the grey level is appropriately modified to represent binary data.
GLM Steganography uses the concept of odd and even numbers to map data within an image. It is a one-to-one mapping between the binary data and the selected pixels in an image.
14. INDIN04 Berlin, 25 June 04 14 Grey Level Modification Algorithm