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industrial Visit ( Defence Research & Development Organization )
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Steganography is essentially a security measure for passing concealed messages, so as the message will not be detected. The goal of steganography is to hide the fact that the message exists. Steganography, which comes from the Greek language, meaning covered or secret writing, is the art of hiding information such as a message within images, audio, text and video. Steganography encompasses methods of transmitting secret messages through innocuous cover carriers in such a manner that the very existence of the hidden message is undetectable.
This project aims at the implementation of the concept of steganography.There are many methods of implementation of this concept available to us but the method I have used here is ?The LSB substitution method?. These techniques are based on modifying the least significant bits (LSBs), of the pixel values in the space domain. In a basic implementation, these pixels replace the entire LSB-plane with the stego-data; on average, 50% of the LSBs are flipped .It can be shown that fidelity of the stego-image measured in peak-signal-to-noise ratio with respect to the cover is 51.1dB, representing a very high degree of imperceptibility compared to the lower bound of 39dB generally accepted by researchers of watermarking. With more sophisticated schemes in which embedding locations are adaptively selected, depending on human vision characteristics, even less distortion is achievable. Popular tools include EzStego, S-Tools, and Hide and Seek.
In general, simple LSB embedding is susceptible to image processing, especially lossy basic LSB approach. Bit-planes of a grayscale image are sketched on the left with MSB on top. Dark and light boxes represent binary values 0s and 1s, respectively, of the pixels on different bit-planes. The LSB-plane of the cover image on the top right is replaced with the hidden data in the middle, which becomes the LSB-plane of the stego-image.
Various steganographic tools have been developed, many available online. In a sense, some simple methods are already defeated due to the relentless endeavor of steganalysts. Meanwhile, countermeasures against steganalysis are also emerging.
Tools that can withstand, to some degree, both visual and statistical attacks are being introduced. For example, in data embedding, much effort has gone toward preserving the statistical characteristics of the cover media. To combat steganalytic tools based on analyzing the increase of unique colors in an image, new embedding methods may be devised that avoid creation of new colors. Alternatively, modifications leading to detectable artifacts may be compensated for after embedding while ensuring the intended recipient is still able to extract the secret message.
Apart from their law enforcement/intelligence and anti-terrorist significance, steganographic techniques also have peaceful applications, including: in-band captioning; integration of multiple media for convenient and reliable storage, management, and transmission; embedding executables for function control; error correction; and version upgrading. Computer specialists, signal-processing researchers, and information security professionals should expect to devote much more attention to the challenging area of information hiding and detection.
IN this era of digital information, huge amounts of digital multimedia data are being transmitted over the internet every single second. However, there may be some confidential messages that are of special type of importance and thus need to be protected during transmission. Hence how to protect a secret message during transmission is a focus of attention.Steganography is a simple and popular way of providing protection for secret messages digitally. In steganographical schemes, digital images are often used as host images due to their popularity on the Internet. The original image in which people hide the secret data is called ?THE HOST IMAGE?.

When the hiding process is completed, the host image has been slightly changed. We called the changed image ?THE STEGO IMAGE?. In this project it has been referred as ?THE MODIFIED IMAGE?. In data hiding techniques, the term ?IMAGE QUALITY? refers to the quality of the stego image, and the term ?HIDING CAPACITY ?indicates the largest quantity of secret data that can be embedded in the stego image.

If a stego or the modified image has good image quality, it can avoid being suspected during the transmission of the hidden secret.
Therefore, data hiding techniques should satisfy the following requirements:-

The stego or the modified image should not appear to have gone under manipulation. This means that when one sees the image he must feel the image to be just an another image in transmission. This lets the image not being suspected in any reason .This characteristic of the stego or the modified image is desired to be in the highest grade or degree.

The number of secret bits that can be hidden into the host image should be as large as possible. It is a desired thing that the size of the secret data file must be smaller then the host image or the original image file (in the project we have taken the host image to be at least 8 times larger then the secret data file).This is done so as to increase the size and the quantity of the data which can be hidden in the host or the original image. As large the size of the host image is, more the quantity of the data that can be hidden in the host image and thus more is the amount of secret information that can be sent via the host image.

The embedded secrets must be secure. This simply means that the secret message cannot be extracted by the illegal user. When one sees the image he must feel the image to be just an another image in transmission. Also the method which is used must be secret enough to accomplish the desired task. In this project we have used the LSB substitution method


There are many kinds of data hiding techniques proposed to achieve the purpose of secure data transmission .However, according to the different kinds of images, their data hiding strategies are also different. For multi-tone images, one simple method is the least significant bits (LSB) hiding scheme. In the LSB method, the secret message is embedded into the host image by replacing the least significant bits of each pixel. As for the binary images, they often embed the secret(s) into the boundary regions rather than black or white regions. With regard to the half tone images, the secret(s) are often hidden into non-clustering regions.

Besides, data hiding techniques can be categorized into two types:
1.) Methods in the spatial domain
2.) Methods in the frequency domain.

In the spatial domain, the secret messages are embedded in the image pixels directly. On the other hand, in the frequency domain, the host image is first transformed into its frequency domain by using discrete cosine transformation (DCT) or discrete wavelet transformation (DWT), and then the secret messages are embedded in the transformed coefficients.

In 1998, Wu and Tsai proposed a spatial domain data-hiding technique on the basis of multiple-base number conversion. In their scheme, they find the differences between the host image and the decompressed host image. The secret bits are then ?embedded? into those differences by applying the multiple base number conversion .The main advantage of their scheme is its simplicity, but the image quality is not good enough.

In 2002, Chao et al proposed a data hiding scheme for hospital electronic data exchange. Being slightly more complex then the Wu-Tsai scheme, their scheme is similar to the Wu-Tsai scheme in that both are based on the number conversion. The multiple base number conversion performs several division operations so that the scheme is not easily implemented on the computer hardware.
Besides, the residue of each division operation cannot be always controlled in small scale. The scale affects the image quality.

The very concept of the project was inspired from the paper by the journal named ?IEE PROCEEDINGS: IMAGE AND SIGNAL PROCESSING? .The paper was titled ?HIDING DATA IN MULTITONE IMAGES FOR DATA COMMUNICATIONS?. The paper was published in the April 2004 issue. The authors of this paper are Mr.C.C.Chang, Mr.J.C.Chuang and Mr. Y.P.Lai. who are currently working with ?THE DEPATRMENT OF COMPUTER SCINCE AND INFORMATION ENGINEERING, NATIONAL CHUNG CHENG UNIVERSITY, TAIWAN, and REPUBLIC OF CHINA

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