RE: Steganography (Download Full Report And Abstract)
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The Steganography is used for secret data transmission. Steganography is derived from the Greek word steganos which means “covered” and graphia which means“writing”, therefore Steganography means “covered writing”. In steganography the secret image is embedded in the cover image and transmitted in such a way that the existence of information is undetectable. The digital images, videos, sound files and other computer files can be used as carrier to embed the information. The object in which the secret information is hidden is called covert object. Stego image is referred as an image that is obtained by embedding secret image into covert image. The hidden message may be plain text, cipher text or images etc. The steganography method provides embedded data in an imperceptible manner with high payload capacity. Encrypting data provides data confidentiality, authentication, and data integrity. Steganography, copyright protection for digital media and data embedding are the data hiding techniques. Steganography is a method of hiding secret information using cover images. Copyright marking classified into watermarking and fingerprinting.
Watermarking is the process of possibly irreversibly embedding information into a digital signal. The signal may be audio, pictures or video etc. Fingerprinting attaches a serial number to the copy of digital media. Copyright protection prevents illegal transfer of data. In data embedding systems the receiver will know about the hidden message and the task is to decode the message efficiently.
The main aspect of steganography is to achieve high capacity, security and robustness. Steganography is applicable to (i) Confidential communication and secret data storing(ii) Protection of data alteration (iii) Access control system for digital content distribution, (iv) Media Database systems etc. The various steganographic techniques are:
(i) Substitution technique: In this technique only the least significant bits of the cover object is replaced without modifying the complete cover object. It is a simplest method for data hiding but it is very weak in resisting even simple attacks such as compression, transforms, etc.
(ii)Transform domain technique: The various transform domains techniques are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Fast Fourier Transform (FFT) are used to hide information in transform coefficients of the cover images that makes much more robust to attacks such as compression, filtering, etc.
(iii) Spread spectrum technique: The message is spread over a wide frequency bandwidth than the minimum required bandwidth to send the information. The SNR in every frequency band is small. Hence without destroying the cover image it is very difficult to remove message completely.
(iv)Statistical technique: The cover is divided into blocks and the message bits are hidden in each block. The information is encoded by changing various numerical properties of cover image. The cover blocks remain unchanged if message block is zero.
(v) Distortion technique: Information is stored by signal distortion. The encoder adds sequence of changes to the cover and the decoder checks for the various differences between the original cover and the distorted cover to recover the secret message
The development in technology and networking has posed serious threats to obtain secured data communication. This has driven the interest among computer security researchers to over come the serious threats for secured data transmission. One method of providing more security to data is information hiding. The approach to secured communication is cryptography, which deals with the data encryption at the sender side and data decryption at the receiver side. The main difference between steganography and cryptography is the suspicion factor. The steganography and cryptography implemented together, the amount of security increases. The steganography make the presence of secret data appear invisible to eaves droppers such as key loggers or harmful tracking cookies where the users keystroke is monitored while entering password and personal information.
Neil F. Johnson and sushiljajodia et al.,  have provided several characteristics in information hiding methods to identify the existence of a hidden messages and also identify the hidden information. The images are reviewed manually for hidden messages and steganographic tool to automate the process. The developed tool is to test robustness of information hiding techniques in images such as warping, cropping rotating and blurring.
Giuseppe Mastronardi et al.,  have studied the effects of Steganography in different image formats (BMP, GIF, JPEG and DWT) and proposed two different approaches for lossless and lossy image. They are based on the creation of an “adhoc” palette for BMP and GIF images.
Tong and QIU Zheng-ding  have proposed a Quantization-based Steganography scheme. In this method the secret message is hidden in every chrominance component of a color image and the hiding capacity is higher than that of the popular Steganography software. Since the Quantization-based hiding method is free from the interference and simulation results the hidden message can be extracted at low BER and our scheme is robust to common attacks.
Jessica Fridrich et al.,  have proposed a new higher-order Steganalytic method called Pairs Analysis for detection of secret messages embedded in digital images. Although the approach is in principle applicable to many different Steganographic methods as well as image formats, it is ideally suited to 8-bit images, such as GIF images, where message bits are embedded in LSBs of indices to an ordered palette. The Ezstego algorithm with random message and optimized palette order is used as an embedding archetype on which we demonstrate Pairs Analysis and compare its performance with the chi-square attacks.
Yuan-Yu Tsai and Chung-Ming Wang  have proposed a novel data hiding scheme for color images using a BSP tree.This method shows high capacity with little visual distortion. Furthermore, there is an advantage of the tree data properties to improve the security of embedding process, making it difficult to extract the secret message without the secret key provided.
Jun Zhang et al.,  have proposed detection of steganographic algorithms based on replacement of the Least Significant Bit (LSB)plane. Since LSB embedding is modeled as an additive noise process, detection is especially poor for images that exhibit high-frequency noise.
M.Mahdavi et al.,  presented a steganalysis method for the LSB replacement. The method is based on the changes that occur in histogram of an image after the embedding of data. It is less complex and more accurate than the RS steganalytic method for the images which are acquired directly from scanner without any compression. The RS method needs to count the number of regular and singular groups twice and also require LSB flipping for the whole image. This method has better average and variance of error comparing to RS steganalytic method
Jan Kodovsky and Jessica Fridrich  worked out the specific design principles and elements of steganographic schemes for the JPEG format and their security. The detect ability is evaluated experimentally using a state of art blind steganalyser.
L.Y. Por et a, proposed a scheme embeds a larger-sized secret image while maintaining acceptable image quality of the stego-image and also improved image hiding scheme for grayscale images based on wet paper coding.
OBJETIVE OF THE REPORT
To design a novel image steganography technique based on discrete wavelet transform and to analyze its efficiency and security using various attacks.
ORGANISATION OF THE REPORT
STEGANOGRAPHY IN HISTORY
Steganography is the art and science of writing hidden messages in such a way that no-one apart from the sender and intended recipient even realizes there is a hidden message. By contrast, cryptography obscures the meaning of a message, but it does not conceal the fact that there is a message. Today, the term steganography includes the concealment of digital information within computer files. For example, the sender might start with an ordinary-looking image file, then adjust the color of every 100th pixel to correspond to a letter in the alphabet—a change so subtle that someone who isn't actively looking for it is unlikely to notice it.