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An Advanced Approach for Implementation of Audio Steganography: Modified LSB Algorithm

An Advanced Approach for Implementation of Audio Steganography: Modified LSB Algorithm

From the graph presented above where mean value is set to 0 we can observe the variation of sampled data values with time. In fig.2, we can see distribution of carrier file, in fig.3, we see distribution by LSB algorithm whereas in fig.4, we see distribution by MLSB algorithm. Our aim behind this graph is to compare the plot of sampled data values of original as well as steno-file. Carrier file acted as a base file for comparison with LSB steno-file and MLSB steno-file. Based on keen observation we can state that the variation of LSB and MLSB steno-file are similar which is comparable to that of original file. So, a listener will not be able to perceive any change among the original file and steno-file.

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Implementation of a Modified LSB Algorithm Based on Pixel Value Differencing for Image Watermarking

Implementation of a Modified LSB Algorithm Based on Pixel Value Differencing for Image Watermarking

To demonstrate the logic of the algorithm, let us take a few data. Let the host pixels be {123 125 226 12} and the watermark pixels be {1 0 0 1}. A threshold value of 10 is chosen. The absolute difference between the first two pixels is |123-125|= 2 which is lesser than the threshold value, thus only one watermark bit is appended in the least significant position of the host pixel. The absolute difference between the next two pixels is |125-226|= 101, which is higher than the threshold value, thus two watermark bits are appended in the least two significant bits of the host pixel which manipulates the data to be 124. The absolute difference of the next two pixels is |226-12|=214 which is greater than the threshold, yet there is only one data is left in the watermark array, thus the last bit is appended in the least significant bit of the host image which makes the value to be 227. Thus the embedded pixel array is {123 124 227 12}.

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Image Steganography Using LSB Algorithm

Image Steganography Using LSB Algorithm

Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image [3]. The least significant bit in other words, the 8th bit of some or all of the bytes inside an image is changed to a bit of the secret message. When using a 24-bit image, a bit of each of the red, green and blue colour components can be used, since they are each represented by a byte. In other words, one can store 3 bits in each pixel. An 800 × 600 pixel image, can thus store a total amount of 1,440,000 bits or 180,000 bytes of embedded data [7]. For example a grid for 3 pixels of a 24-bit image can be as follows:

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A Digital WATERMARKING Algorithm with High Efficiency Based on DWT and LSB

A Digital WATERMARKING Algorithm with High Efficiency Based on DWT and LSB

After Discrcte Wavelet transformation, the use of LSB algorithm have a great impact on the quality of carrier the image and promote the efficiency of embedding and save the space. Experiments show that our algorithm is improved the robustness and high efficiency embedding and anti-clipping digital watermark algorithms based on the LSB, watermark separation and image interpolation has obvious anti-clipping effect.

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Loseless and Reversible Data Hiding Using AES and LSB

Loseless and Reversible Data Hiding Using AES and LSB

The goal of this project to provide the security of user encrypted messages to hide the LSB embedding images using MATLAB code. Using LSB embedding data is embedding in the identified block. The stego image obtained in this process is forwarded to the receiver. The same process is reversed in the receiver side in order to get the secret information that is hided in the image. The performance of the process is measured with the help of the performance metrics like PSNR, MSE and Embedding ratio. The proposed method performances were much improved compared to the existing methods. In the proposed system, the LSB algorithm is used to hide the encrypted data into the Encrypted image.

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Review on Video Steganography

Review on Video Steganography

To maintain the secrecy of information, various information hiding techniques are used. Steganography is one of them, which means hide information inside another digital media like text, image, audio, video etc. without being detected by human visual system. Although many steganographic techniques, in the literature, have been developed for this purpose, most of them distort the quality of the host-signal during data embedding and the changes will be become visible to the human eye especially for those signals distributed via the Internet which must be processed by a low bit rate compression due to bandwidth limitations. Therefore, the challenge is to create a steganographic technique that is able to hide acceptable amount of data without altering the quality of the host-signal. This paper presents the steganography of an Image on a multiple frame video using Frame Decomposition Technique in which LSB Algorithm is used on multiple frame video for Steganography. The aim of the research is to get image so image decomposition is required for this type of steganography. It declares that same image which steganography has been done will extract at output phase. Message hiding technique using LSB algorithm has been used.

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A Secure Image Based Steganographic Model Using RSA Algorithm and LSB Insertion

A Secure Image Based Steganographic Model Using RSA Algorithm and LSB Insertion

the pixel bytes in an image. The comparisons are made starting from the first byte in the image until the last byte that permits all the data to be hidden in that image. The application cycles through the pixels of the image looking for the block of bytes that result in the least number of LSB changes. The image is then given a rank based on the percentage of least significant bits that match the encrypted data bits. Consider, for example 10 bits of encrypted data that need to be hidden in an image with a bit pattern of 10000000001. If some block of bytes in the image has least significant bits with a pattern 1000000011, this would result in the image receiving a ranking of 90%, because nine of the ten bits are an exact match.

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Image Steganography using Secured Force Algorithm for Hiding Audio Signal Into Colour Image

Image Steganography using Secured Force Algorithm for Hiding Audio Signal Into Colour Image

create the need for secured transmission of secret message, data or information. There exist several methods for providing secured transmission of information. The most attractive and latest approach for information security is steganography. Steganography is the practice of hiding any text data, image, audio or video within another image, audio or video. The main aim of this paper is to hide audio signal into colour image using AES algorithm and circular LSB algorithm. And this embedded output is secured using secured force algorithm which provide another layer of security. At decryption side ADS algorithm provides decrypted output. This image steganography provides hiding of data more effective and efficient manner with help of circular LSB and secured force algorithm.

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Efficient Data Hiding System using Cryptography and Steganography

Efficient Data Hiding System using Cryptography and Steganography

[11] in their research proposed two approaches for secured image steganography using cryptographic techniques and type conversions. One of the methods shows how to secure the image by converting it into cipher text through S-DES algorithm using a secret key and conceal this text in another image using steganographic method. The second method shows a new way of hiding an image in another image by encrypting the image directly through S-DES algorithm using a key image and the data obtained is concealed in another image. The flows of the two approaches are shown in figure 2 and 3:

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A NOVEL ALGORITHM FOR CRYPTOGRAPHIC KEY GENERATION BASED ON SESSION AND STEGNOGRAPHY

A NOVEL ALGORITHM FOR CRYPTOGRAPHIC KEY GENERATION BASED ON SESSION AND STEGNOGRAPHY

A key is used to encrypt or decrypt the message. At the sender side, plain text is converted into cipher text using the key. At the receiver end, key is used to decipher the cipher text into plain text. Image is selected from the database on the basis of session (hourly or daily). Then the difference in the LSB of the image pixels is used to generate the secret key. This key is used by both the sender and receiver for encryption and decryption process respectively. The length of the key generated is not fixed and depends on the message size.

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DESIGN, ANALYSIS AND OPTIMIZATION OF A MICROSTRIP PATCH ANTENNA AT FREQUENCY 
3 55 GHZ FOR WIMAX APPLICATION

DESIGN, ANALYSIS AND OPTIMIZATION OF A MICROSTRIP PATCH ANTENNA AT FREQUENCY 3 55 GHZ FOR WIMAX APPLICATION

Steganography derived from Greek, literally means “hidden-writing”. It is an art and science of hidden communication i.e. it hides the existence of communication itself. The goal of Steganography is to embed the secret information into other information. Thus it hides the existence of communicated secret information. Steganography is often confused with Cryptography because both are used to protect information. While the goal of Cryptography is to conceal the data to be communicated, the goal of Steganography is to conceal the existence of communication. The basic model of Steganography consists of a cover object, a secret message that is to be transmitted and an algorithm to hide the message in the cover object. In many cases a stego-key is also used to encode the secret message for providing more security. The result of this method is a stego-object which contains the secret message. Now this stego-object can be used in communication. At the receiver’s side, this stego-object is received and is decoded by

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Image Steganography using Variable Key Technique for Double Tier Security

Image Steganography using Variable Key Technique for Double Tier Security

In this paper for double tier security, the variable keys are generated and encrypted data is hidden in cover image using Modified LSB Algorithm. The proposed algorithm has improved MSE and PSNR values as compared to existing Modified LSB technique. Thus the algorithm built in this combination of steganography and cryptography is personalized that it clues none but privacy and robustness.

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Video Watermarking using YCBCR and RLE

Video Watermarking using YCBCR and RLE

To overcome the disadvantages of the conventional techniques and to increase the data security, the watermark is first encrypted. Techniques like RLE, LZW, can be employed for securing & compressing the data. Encrypting watermark improves the security of the system. Now, more data can be saved as now embedded watermark is in compressed form. This proposed technique will be more secure and robust than the conventional techniques. YCbCr color space conversion is used. The proposed methodology is divided into two sections. One is the embedding of the data into the video and other section is the extraction of data from the video. In this proposed methodology the RLE encoding algorithm is used for the data compression and LSB technique is used for the hiding of data. Methodology of the data embedding process is as follows:

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Obscuring the Message in Digital Image Using Steganography

Obscuring the Message in Digital Image Using Steganography

After encryption of the message using AES algorithm, [2] the encrypted text is converted into ASCII equivalent form which then converted to binary data format. For example, if the encrypted letter is “k” its equivalent ASCII value is 107 and binary equivalent is 01101011. This binary value is embedded in an image by using the embedded using the LSB technique.

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A ROBUST COLOR IMAGE WATERMARKING TECHNIQUES WITH CONTRAST ENHANCEMENT

A ROBUST COLOR IMAGE WATERMARKING TECHNIQUES WITH CONTRAST ENHANCEMENT

Robustness is a default measure which is used to evaluate the performance of watermarking algorithm resistance against attacks such as compression, salt & pepper noise, filtering, cropping, and rotation. In a satisfactory algorithm for image watermark, the watermark would not be easily removed from the watermarked image after common and deliberate attacks.

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A Comparative Study of Transform Based on Secure Image Steganography

A Comparative Study of Transform Based on Secure Image Steganography

From Fig. 6, it can be seen that CTT shows better provable security than the SLT, whereas Haar is still showing slightly better candidate of provable security than CTT. In Fig. 6(b), it is observed that irrespective of image format, Haar based modified Varying LSB scheme is of rank 1 (in the range [0.997, 0.998] showing best results of structural similarity (SSIM), CTT are at rank 2 and SLT are at rank 3. Moreover as BPP increases the Haar based scheme is almost constant (consistent) whereas CTT shows slow downward results from 0.998 to 0.991and SLT is showing sharp fall from 0.998 to 0.984 as compare to other transforms, though all the transforms have acceptable structural similarity.

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Image Steganography using LSB and LSB+Huffman Code

Image Steganography using LSB and LSB+Huffman Code

Steganography is an important area of research in recent years involving a various number of applications. It is the science of embedding information into cover of the media such as text, image, audio, and video. This paper uses two techniques for Steganography (text into image): Least Significant Bit (LSB) and Least Significant Bit with Huffman code (LSB+HUFF). It uses the zigzag scanning for the two methods to increase the security, and compares the results using Peak Signal to Noise Ratio (PSNR). All images used here is a gray scale images to implement the study; what implemented on gray scale image can be applied on colored image.

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Reversible Data Hiding in Color Images Using AES Data Encryption System

Reversible Data Hiding in Color Images Using AES Data Encryption System

The project proposes the enhancement of security system for secret data communication through encrypted data embedding in Color images. A given input image is converted to any one plane process. After plane separation, the encrypted data hider will conceal the secret data into the image pixels. The data hiding technique uses the LSB replacement algorithm for concealing the secret message bits into the input image. In the data extraction module, the secret data will be extracted by using relevant key for choosing the image pixels to extract the data. By using the decryption key, the data will be extracted from Input image to get the information about the data. Finally the performance of this proposal in Color Image and encryption data hiding will be analyzed based on image and Encrypted data. Keywords:-RGB; Encryption, LSB Process; MSE; PSNR

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Comparison of Steganography at One LSB and Two LSB Positions

Comparison of Steganography at One LSB and Two LSB Positions

The plain text in example ii has been considered for encryption and the graphical user interface for two LSB and one LSB have been shown in Fig 3 and 4 respectively. The length of the plain text is 90 characters. Table- 5 shows image parameters for steganography at one LSB and Two LSB positions.Theresults for JPEG and BMP image formats have been verified and the proposed method works fine. Images a, b, c are in the JPEG format and their corresponding stego- images are d, e, f. The images g, h, i are in BMP format and their corresponding stego-images are j, k, l as shown in Fig 5.The statistical analysis for these images has been shown in Table-6. The image parameters like Mean, Standard Deviationand Entropy before embedding and after embedding the text have been calculated. From this statistical analysis it is clear that inserting data at two LSB positions hardly changes the carrier image parameters also the quality of the image is retained.

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An Adaptive Stegnography Method for Hiding Message Using LSB Matching Algorithm

An Adaptive Stegnography Method for Hiding Message Using LSB Matching Algorithm

Image steganography has gotten more popular press in recent years than other kinds of steganography, possibly because of the flood of electronic image information available with the advent of digital cameras and high-speed internet distribution. Adaptive LSB substitution method is used to hide data efficiently and securely in an image. In this paper, various types of images are used as cover image and all types of data such as video, audio, etc has been stored and retrieved with good accuracy. Adaptive LSB technique performs more efficiently in both security and accuracy aspects than the traditional LSB technique. Another method which we were unable to explore was to analyze the noise of the pictures. Adding hidden data adds random noise, so it follows that a properly tuned noise detection algorithm could recognize whether or not a picture had steganographic data or not. This paper manipulates the spatial data of cover image. By using the properties of the DCT, the frequencies can be efficiently used to hide the secret data which is also more resisitant to noises.

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