Reversible Data Hiding Scheme Using Turbo Code

This paper presents a steganographic scheme based on the RGB colour cover image. The secret message bits are embedded into each colour pixel sequentially by the pixel-value differencing (PVD) technique. PVD basically works on two consecutive non-overlapping components; as a result, the straightforward conventional PVD technique is not applicable to embed the secret message bits into a colour pixel, since a colour pixel consists of three colour components, i.e. red, green and blue. Hence, in the proposed scheme, initially the three colour components are represented into two overlapping blocks like the combination of red and green colour components, while another one is the combination of green and blue colour components, respectively. Later, the PVD technique is employed on each block independently to embed the secret data. The two overlapping blocks are readjusted to attain the modified three colour components. The notion of overlapping blocks has improved the embedding capacity of the cover image. The scheme has been tested on a set of colour images and satisfactory results have been achieved in terms of embedding capacity and upholding the acceptable visual quality of the stego-image.

Reversible data hiding (RDH) is an active research area in the field of information security. The RDH scheme allows the transmission of a secret message by embedding it into a cover image, and the receiver can recover the original cover image along with the extraction of the secret message. In this paper, we propose a bit plane compression based RDH scheme to hide a sequence of secret message bits into a grayscale image. In the proposed method, a selected bit plane of the cover image will be compressed using run-length encoding (RLE) scheme. Further, the RLE sequence has been efficiently encoded as a binary sequence using Elias gamma encoding method. The Elias gamma encoded bit sequence concatenated with the secret message bits are used to replace the selected bit plane after performing a sequence of Arnold transform. The Arnold transform helps to find a new scrambled version of the bit plane which is very close to the original bit plane to ensure the visual quality of the stego image. The RLE is a lossless compression technique, therefore recovery of the original image is possible by the receiver. The experimental study of the proposed scheme on the images from standard image dataset (USC-SIPI image dataset) shows that the proposed scheme outperforms the existing scheme in terms of the visual quality of the stego image without compromising the data embedding rate.

In spatial domain image steganography, Least Significant Bits (LSB) of cover image pixels are used to embed a secret message due to minimal distortion and higher payload capacity. In this paper, we have introduced an exclusive-OR (XOR) based encoding of encrypted secret message bits using varying higher-order pixel intensity bits. Encoding and LSB embedding is done block-wise by dividing the cover image into a number of blocks. The secret message is first encrypted using symmetric key cryptography and then encoded those encrypted bits by XORing them with randomly selected higher-order pixel bis of the cover image to obscure the secret bits further. Next, an inversion technique is applied to the encoded bits block-wise to keep the LSB bit changes to a minimum. The stego-key consists of the symmetric encryption key and the encode-key containing parameter settings such as the number_of_blocks, starting_block, start_pixel_offset, block_selection_rule, etc. This stego-key is shared prior to the actual communication using public-key cryptography to ensure the key’s authenticity and integrity. The extraction process does not require the cover image; the stego-image and the stego-key are sufficient. Experimental results show the visual imperceptibility along with improved image quality metrics such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Normalized Cross-Correlation (NCC), and Structural Similarity (SSIM) index in comparison to other well-known techniques. The average PSNR value remains above 51dB, even with 90% of the capacity utilized. The proposed scheme successfully eludes many standard steganalysis attacks such as histogram-based analysis (PDH), chi-square based embed probability test, Regular and Singular groups (RS) analysis, sample pair test, etc. on the tested stego-images.

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), and comparison to findings from related prior efforts.

Turbo codes (TC) is a powerful branch of error-control coding that has exhibited performances close to the Shannon limit, whilst offering a reasonable level of computational complexity. Repeat-punctured turbo codes (RPTCs) exploit the fact that the use of larger interleavers correspond to better bit-error rate (BER) performances for the conventional turbo code, and makes use of repetition and puncturing to improve the performance of the conventional turbo code for moderate to high signal-to-noise ratios (SNRs). Motivated by turbo codes and repeat-punctured turbo codes, we study the use of a new scheme, dual-repeat-punctured turbo codes (DRPTC) in the additive white Gaussian noise (AWGN) channel. DRPTCs primarily make use of repetition and puncturing and the structure of the conventional turbo code to yield a more superior performance. The decoding in principle follows the technique of turbo decoding but needs some changes to yield the performance improvement. Simulation results for the AWGN channel is presented together with the analytical union bounds derived from transfer-function bounding techniques, and the codeword distance-spectrum for the proposed scheme is presented and evaluated.

It is well known that binary error-correcting codes with iterative decoders can achieve near Shannon-limit performance on the additive white Gaussian noise (AWGN) channel, but their performance on more realistic wireless channels can become degraded due to the presence of burst errors or impulsive noise due to interference. A better performing coding scheme is the class of non-binary codes, which are known to be more effective in correcting burst errors, but interestingly there is no research reported in the literature investigating non-binary codes on impulsive noise channels. In this paper, we investigate the performance of non-binary turbo codes defined in a finite field GF(4) on symmetric alpha-stable impulsive noise channels and compare with comparable binary turbo codes. A Cauchy receiver is also employed to mitigate the effects of the channel to assist the turbo decoding. Our simulation results show that although the non-binary turbo code performs similarly to the binary turbo code on the AWGN channel, it achieves a significant coding gain over the binary turbo code as impulsiveness increases.

Security in communication is a top priority in the use of steganography. This concept allows us to convey messages to people we want through a media without arousing suspicion to others. In this case the media used is digital media. More specifically digital media used are image media because images are the most popular media in secret message hiding. The increasingly widespread use of the internet as a communication medium is the reason why this message insertion technique uses the PHP programming language that is currently popular as a programming language supporting web-based applications. The LSB (Least Significant Byte) method is a message hiding technique in steganography where the hidden message is hidden by replacing the data bits in the image segment with secret message bits. Secret message bits are inserted in the low bit or the rightmost bit in the pixel composing the image consisting of red, green and blue (RGB), each of which has an 8-bit value of 0 to 255 with binary format 00000000 to 11111111. Thus, 3 bits of data can be inserted in each pixel image available. The LSB method is then applied in a library which is then named as a stegger which has the function to insert messages in images using the PHP programming language. To add protection to messages sent, an encryption algorithm is added that has been arranged in a class named secrypt that is accompanied by keyword inclusion so that the message sent has a higher level of security. Â Keywords : steganography, PHP, encryption, stegger, secrypt

This correspondence analyzes the performance of concatenated coding systems and modulation schemes operating over the additive white Gaussian noise (AWGN) channel by examining the loss of capacity resulting from each of the processing steps. The techniques described in this correspondence allow the separate evaluation of codes and decoders and thus the identification of where loss of capacity occurs. Knowledge of this capacity loss is very useful for the overall design of a communications system, e.g., for evaluating the benefits of inner decoders that produce information beyond the maximum-likelihood (ML) estimate. The first two sections of this correspondence provide a general technique for calculating the composite capacity of an orthogonal or a bi-orthogonal code and the AWGN channel in isolation. The later sections examine the composite capacities of an orthogonal or a bi-orthogonal code, the AWGN channel, and various inner decoders including the decoder estimating the bit-by-bit probability of a one, as is used in turbo codes. The calculations in these examples show that the ML decoder introduces a large loss in capacity. Much of this capacity loss can be regained by using only slightly more complex inner decoders, e.g., a detector for M-ary frequency-shift keying (MFSK) that puts out the two most likely frequencies and the probability the ML estimate is correct produces significantly less degradation than one that puts out only the most likely frequency.

In this work, we propose a steganographic scheme for embedding secret message in VQ-compressed images, which aims to achieve high embedding capacity while keeping distortion low. To achieve these objectives, we develop a progressive exponential clustering (PEC) algorithm for partitioning the VQ codebook into a set of clusters. To embed the secret message based on the clustering, we substitute the indexes of the codewords with others within the same cluster according to the size of the cluster and the secret message bits.

This paper presents hiding one to eight gray images or texts (secret information) inside color image (cover image) based on Least Significant Bits (LSB) algorithm. The main idea is to insert the secret message (one to eight texts or one to eight gray images) in the three LSB of the cover image (color image). The color cover image RGB model (R channel, G channel and B channel) is separated into three cover images (the red cover, green cover, and blue cover). Each one of these three cover images is used to hide secret messages (gray image (two secret images in R channel, three secret images in G channel and three secret images in B channel) or text). The experiments and comparative studies show that the algorithms are characterized by many features of the ability of hiding huge data, and then the ability of extracting secret message without errors. Beside the reconstructed image, has efficacies (to human acquaintance) according to peak signal to noise ratio (PSNR) and mean square error (MSE), also retain both the explicitness and the characteristics of the both secret message and cover image.

Steganography is a data security technique that used as an effort to secure data. Various techniques and media tested in the steganography technique. One of the classic methods that still today is the Least Significant Bit (LSB) method. As one of the classical methods, this method tested in many technical modification developments and tested on various types of cover media. Various LSB methods that have done always show changes in quality. Therefore, this study conducted tests to try to increase the capacity of the steganography and test the quality degradation that occurred using LSB and some modified LSB methods. The evaluations include calculating the PSNR value, drawing the visual spectrogram, and calculating the BER value. The PSNR evaluation shows that the larger the cover media size used, the smaller the risk of quality degradation, and the bigger the secret message, the greater the noise that will be generated. The evaluation of BER shows that any technique depends on the match between the cover media bits and the secret message bits. Evaluation of the calculation of the maximum steganographic capacity shows that the larger the size of the cover media, the greater the capacity of the secret message that the cover media has.

How to embed more secret message into web page with keeping good imperceptibility simultaneously is a trade-off problem for information hiding schemes. This paper presents a novel web page information hiding method based on three inherent features of current web page's HTML Code matrix. This method firstly exploits chaotic transform to deal with secret message, then embeds each bit of secret message into cover web page according to the random odevity of character amount contained by each row(column) in cover web page's HTML code matrix. Its process is very simple to understand and easy to implement. It can improve the largest embedded capacity (LEC) of cover web page greatly with keeping good imperceptibility at the same time. We test our approach on two test data sets which include 1000 web pages in total. The experiment results show that the max LECs for these two data sets are up to 11291 bits and 13545 bits respectively. The average LECs for two data sets has improvement of 80.2% and 24% more than that of other web page information hiding method .


 
 
 A hybrid steganographic technique has been proposed to enlarge the size of secret message and to hide several images in one cover image. Initially, the secret images were compressed using JPEG 2000 before embedding them to the cover image. Second least significant bit plane of cover image was entirely replaced by secret message while tri-ways-pixel-value-differencing (TPVD) was used to hide secret message in remaining seven-bit cover image. The quality of stego image was enhanced by residual image coding (RIC). The cover image was divided in four sub-images, three of them provided cover for secret message using proposed technique while fourth sub-image was used to embed RIC of stego image using only TPVD, to ensure better quality in terms of peak signal to noise ratio (PSNR). Proposed technique provided the opportunity to transmit secret data without detection by different steganalysis techniques like dual statistics steganalysis. Experimental results verified that proposed technique achieved high payload with better image quality than TPVD scheme.
 
 

The use of open-loop coding can be easily extended to a closed-loop concatenated code if the transmitter has access to feedback. This can be done by introducing a feedback transmission scheme as an inner code. In this paper, this process is investigated for the case when a linear feedback scheme is implemented as an inner code and, in particular, over an additive white Gaussian noise (AWGN) channel with noisy feedback. To begin, we look to derive an optimal linear feedback scheme by optimizing over the received signal-to-noise ratio (SNR). From this optimization, a linear feedback scheme is produced that is asymptotically optimal in the sense of blocklength-normalized SNR; it is then compared to other well-known schemes. Then, the linear feedback scheme is implemented as an inner code to a concatenated code over the AWGN channel with noisy feedback. This code shows improvements not only in error exponent bounds, but also in bit error rate (BER) and frame error rate (FER). It is also shown that if the concatenated code has total blocklength L and the inner code has blocklength, N, the inner code blocklength should scale as N = O(C/R), where C is the capacity of the channel and R is the rate of the concatenated code. Simulations with low-density parity-check (LDPC) and turbo codes are provided to display practical applications and their error rate benefits.

The main problem: The article deals with the issues of hiding text information in a graphic file. A formula for hiding text information in image pixels is proposed. A steganography scheme for embedding secret text in random image pixels has been developed. Random bytes are pre-embedded in each row of pixels in the source image. As a result of the operations performed, a key image is obtained. The text codes are embedded in random bytes of pixels of a given RGB channel. To form a secret message, the characters of the ASCII code table are used. Demo encryption and decryption programs have been developed in the Python 3.5.2 programming language. A graphic file is used as the decryption key. Purpose: To develop an algorithm for embedding text information in random pixels of an image. Methods: Among the methods of hiding information in graphic images, the LSB method of hiding information is widely used, in which the lower bits in the image bytes responsible for color encoding are replaced by the bits of the secret message. Analysis of methods of hiding information in graphic files and modeling of algorithms showed an increase in the level of protection of hidden information from detection. Results and their significance: Using the proposed steganography scheme and the algorithm for embedding bytes of a secret message in a graphic file, protection against detection of hidden information is significantly increased. The advantage of this steganography scheme is that for decryption, a key image is used, in which random bytes are pre-embedded. In addition, the entire pixel bits of the container image are used to display the color shades. It can also be noted that the developed steganography scheme allows not only to transmit secret information, but also to add digital fingerprints or hidden tags to the image.