Information Hiding Techniques for Steganography and Digital Watermarking, can be stored in different formats (like HTML, 's DVI, Postscript, PDF, or RTF);. PDF | Until recently, information hiding techniques received very much Optimal Secure Information using Digital Watermarking and Fuzzy. Information Hiding Techniques for Steganography and Digital Watermarking . A new approach to covert communication via PDF files, Signal Processing, v
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data hiding in media. • We mainly use images but techniques and concepts Digital Watermarking.» Steganography Information hiding differs from traditional communication systems in and the stego object pdf's is at most: • Perfectly. Abstract: Information hiding techniques have recently become important in a There are two main types of digital speech watermarking. use of files in an electronic format new techniques for information hiding have watermarking and fingerprinting which will be discussed later. Proposal on Information Hiding Methods using XML, gonddetheppolad.ga
This type of image has good quality, and the number of palettes is more than 16 million different color . Most of these extensions use RGB format to show intensity of pixel color. This means each pixel has six hexadecimal digits.
Images are of different sizes, which depend totally on the number of pixels and also on the number of bits in each pixel. It is necessary to reduce image file sizes when transmitting via the internet. For this purpose many compression methods were developed over recent years. The two most popular types of compression are lossy and lossless compression, which are widely used in image processing. Lossy compression scheme uses by JPEG images this technique try to expand the file near to the size of original file .
On the other hand, lossless compression is a scheme that uses to rebuild the original image by applying some software. In other words, if the original data is an image, processing would be into the pixel values without changing the data into another domain. The widest and simplest method in spatial domain is Least Significant Bit LSB , which is replacing the first bit in each pixel by information that intends to hide .
Information Hiding: Steganography and Watermarking
Least Significant Bit Watermarking LSB is the one of the oldest and simplest algorithms that allows users to hide their information using spatial domain [16; 38]. The human eye cannot recognize the difference that occurs in the two first bits in each pixel. This provides users with more storage capacity to embed the information that is necessary to hide.
For example, two pixels of an RGB image color will provide six bits for watermarking. Pixel1: Pixel2: Pixel3: Pixel4: Pixel5: Pixel6: Frequency Domain Watermarking This is also called transform domain, because the original data changes from spatial to frequency domain.
For example, an 8-bit image with a by resolution can be transformed into frequency watermarking using DWT.
The result of this processing would be four small images, each of them with a by resolution. Moreover, four images will have different frequency ranges from low to high because each of them has different coefficients for others. The main advantage of using frequency domain watermarking is that it is robust for many kinds of signal manipulations when sending data via the Internet. Also, it resists of many noises that attack embedded information [2; 13; 31].
Discrete Wavelet Transform It is a tool to transform the signal or data from one domain which is a spatial to another domain which is a frequency. In the frequency domain the signal splits into the two half one of them is high frequency and another is low frequency. Then each of them is going to divide again into high and low frequency that four different parts of signal .
Four parts or sub bands of decomposed signal are LL, LH, HL and HH frequencies which are low-low, low-high, high-low and high-high frequencies [10; 29]. Low frequency is the same of original signal and other parts are more details of signal they are not exact data as original one, so we can change or remove depends on the technique that we using.
The reconstruction process is the opposite of decomposition process that means the four bands of divided data have to be mixed again to recover the original data. Sometimes we do more than one level of decomposition depends on the algorithm that we use.
Low-low frequency band will be used in case we do second decomposition. In case of reconstruction the last level of decomposition will used first which is an exact opposite direction .
Then, applying a discrete cosine transform on each block will convert the signal into high, middle and low frequencies. Low frequency is very close to original data while the middle and high frequencies are more details of the data. We can use the details frequencies as a host data to hide some important secret on it or we can remove those details frequencies to reduce the size of the signal.
The reconstruction process is rebuilding the signal in opposite way it means combining all frequencies high, middle and low into single signal . Embedding and Detection Processes In embedding process the secure data which called the logo will be embedded into the host data sometimes call cover data and send to the destination. User can use many secret keys; in general we can divide into two types. First, symmetric key which both sender and receiver have the same key for encryption and decryption data.
Second, asymmetric key both transmitter and receiver use different types of keys.
Watermarked data is the data that has to be sent to destination which consists of mixing logo, cover and key data which seems to anyone that is one piece of data . Figure2 shows embedding process. Watermark Embedding Process  p.
In detection process, when the watermarked data reaches to the destination as one piece of data which in reality it is a group of mixed data.
The logo data will be extracted from the mixed data by using one type of key. Splitting of those three signals needs to use one of techniques in both spatial and frequency domains. The extraction process depends on the type of the algorithm that used and the quality of recovered signals is different from using one algorithm to others. Also the number of decomposition levels that used in embedding process affects directly to the quality of the data that have been sent it by user which is using the same number of reconstructions levels .
Figure3 shows detection process. Watermark Detection Process  p.
Many techniques have been invented since these problems appeared. One useful technique to protect information via the internet is steganography. Digital watermarking is one of the popular applications for steganography.
Users can hide important information within an image by using an invisible watermark when they transmit data. Moreover, a visible watermark can be used in many applications such as author, creator, and document. Images have some unimportant regions the human visual system cannot recognize by replacing these regions with other information.
Security and Communication Networks
Also, this alteration does not affect the intensity of the color. Adaptive steganography scheme using more surrounding pixels.
Applications of the naturalness preserving transform to image watermarking and data hiding. Digital Signal Processing, 14 6 , Colored digital image watermarking using the wavelet technique. Chapter 9: Copyright on the Internet and watermarking Stanley Lai and Fabrizio Marongiu Buonaiuti finally discusses watermarking systems from a legal point of view and addresses various other aspects of copyright law on the Internet.
T he main driving force is concern over protecting copyright; as audio, video and other works become available in digital form, the ease with which perfect copies can be made may lead to large-scale unauthorized copying, and this is of great concern to the music, film, book and software publishing industries.
At the same time, moves by various governments to restrict the availability of encryption services have motivated people to study methods by which private messages can be embedded in seemingly innocuous cover messages. T his book surveys recent research results in the fields of watermarking and steganography, two disciplines generally referred to as information hiding.
Included are chapters about the following topics:. Steganography Software Wiki add your own.
The Codebreakers. Research in Cryptography. Related Systems Issues. site Recommends: Information Hiding: Privacy Information. Johnson and S. Google Scholar  J. Fridrich, M. Goljan, and R. Google Scholar  J.
Google Scholar  G. Lin and W. Google Scholar  I.
A Comparative Analysis of Information Hiding Techniques for Copyright Protection of Text Documents
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Image Process. Provos and P. Google Scholar  I. Cox, J.
Kilian, F. Leighton, and T. CrossRef Google Scholar  M. Jochen, L. Marvel, and L. IEEE, June Google Scholar  W.
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Boncelet, Jr. CrossRef Google Scholar  C. Marvel, and C. Patent 6,,, Google Scholar  J.site Rapids Fun stories for kids on the go. We briefly review quantization in the context of predictive coding here.
The above system is very simple but not useful, since no warden will let Alice and Bob exchange random strings.
Butera, D. At the receiver side the difference signal is dequantized and added to the last signal sample in order to construct an estimate for the sequence x r For steganographic purposes the quantization error in a predictive coding scheme can be utilized; specifically, we adjust the difference signal A. However, a trade-off exists between the amount of information added to the image and the robustness obtained [7, 37].
I Tampering Attacks. The overall size of the cover object also plays a factor as well. The differences, if the carrier is the same, comprise the payload.
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