Performance Improvements of Partial Reversible Data Hiding Scheme

Steganography is a process to conceal the existence of a message. Image Steganography involves hiding the message onto a cover image to obtain a resultant stego image. This paper discusses a procedure for hiding coloured message images onto coloured cover images using a lossy Image Steganography technique. The secret images undergo Discrete Cosine Transformation, quantization and AES encryption before embedding using the Least Significant Bit embedding (LSB) technique onto the cover image. Finally, Peak signal-to-noise ratio (PSNR), Structural Similarity Index measurement (SSIM), zero normalized cross-correlation (ZNCC) are used for comparing the cover and stego images as well as the extracted and original images.

This paper presents a novel reversible data hiding method, which can recover the original image content without distortion from the stego images after the secret data have been extracted. The method utilizes the original cover image to finally generate two visually similar stego images by embedding additional data. During the data embedding process, the pixels in the first stego image are utilized to embed secret data by applying the proposed prefix matching technique, which exploits each of the gray values to carry one or two bits only with ± 1 operation. Pixels in the second stego image are adaptively modified to carry rest secret data by referring to the first stego image using the directed LSB embedding. For the recipient, the additional data can be extracted from the two stego images with the DH key, and the original cover image can be recovered with the location map. If the cover image has no boundary gray-values, one can always recover the cover image from the two stego images without the aid of any extra information. Experiments show that the proposed method can achieve desirable embedding capacity and maintain a high level of image quality.

The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

Data is an asset for all parties. So that it must always be guarded or secured so that it is not misused by irresponsible parties. One of the methods used for data security is steganography. In this paper, efforts to secure data are discussed through the development of steganographic algorithms using the Haar integer wavelet transform (IWT-Haar) and least significant bit (LSB) techniques to hide secret messages in the form of digital text into digital images (cover images) to produce stego images. The results show that the extracting process is much faster than the embedding process. The PSNR values obtained ranged from 55-71,5 dB (far greater than 40 dB). This shows that the resulting stego image is of very good quality. In plain view, the difference between the cover image and the stego image has not changed significantly.Key words: digital image, embedding, extraction, Haar integer wavelet transform, steganographyÂ

Security of information is becoming main criteria while transferring information through communication networks. Nowadays images are used as information source; therefore its security from unauthorized or unintended access is important. Image encryption play an important role in protecting images from hacking and stealing while sending over an unsecured channel. The proposed method is a combination of encryption using Hill cipher algorithm along with Elliptic curve for enhanced security. Elliptic curve cryptographic method is used to make the system to asymmetric from the less secured symmetric key encryption technique; hill cipher algorithm. In our proposed method we use both grayscale images as well as color images regardless its size. Steganography of actual image with a cover image before encryption is an advantage. The cover image is selected as it mocks like an informative to unauthorized access. Least Significant Bit (LSB) steganography method is used here as it provides more security than any other methods.

Steganography, the technology of protecting a secret message by embedding it inside a cover image, continues to be investigated and enhanced as an alternative data protection method. This paper deals with hiding multimedia files in true color RGB cover images with an emphasis on reducing the cover size, increasing hiding capacity and enhancing security of the hidden data. A proposed model (DuoHide) is presented in which a secret multimedia file, regardless of its type, is processed without un-compression, and divided between two cover images of equal size and dimensions. The multimedia file is read as a stream of bytes and split vertically into two parts, one part contains the least significant half-bytes, and the other part contains the most significant half-bytes. The two parts are hidden inside two uncompressed RGB cover images using a least significant 4-bit replacement technique. The resulting dual stego images are expected to be sent separately, through different channels, to avoid capture of both stego files by an adversary. Extraction of the secret file is achieved through merging LSB half-bytes from the two stego files. The extracted file is identical in content and structure with the original secret file. The implemented DuoHide system was evaluated using a set of public multimedia files, images, audios, and videos, of various sizes. The secret file sizes ranged from 5% to about 100% of the cover image's size. The experimental results showed that even at the highest embedding ratio, which is based on the secret-to-cover ratio, there were no perceptible visual differences between cover and stego images. The PNSR value was calculated as PSNR1, for cover1 and stego1, and PSNR2 for cover2 and stego2. The lowest PSNR value was around 31 dB for the highest embedding ratio, which is considered acceptable concerning statistical imperceptibility. The PSNR value increased as the embedding ratio decreased, reaching around 65 Decibel (dB) for the case of 5% secret-to-cover ratio. The integrity of the extracted secret file was verified through a bitwise comparison between original and extracted files, which showed zero differences. The DuoHide model is expected to provide better security for the hidden file, in case an attacker manages to capture one of the stego images and recover the hidden content because the attacker will only get an incomprehensible set of half-byte bits. An additional advantage of using a pair of stego files is that of reducing stego file size by 50%, to avoid problems and limitations of transmitting large files, especially that multimedia files are often large, and they cannot be compressed because they are already compressed. Security of the DuoHide system can further be improved by randomizing storage locations within the two 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.

Digital images are widely communicated over the internet. The security of digital images is an essential and challenging task on shared communication channel. Various techniques are used to secure the digital image, such as encryption, steganography and watermarking. These are the methods for the security of digital images to achieve security goals, i.e. confidentiality, integrity and availability (CIA). Individually, these procedures are not quite sufficient for the security of digital images. This paper presents a blended security technique using encryption, steganography and watermarking. It comprises of three key components: (1) the original image has been encrypted using large secret key by rotating pixel bits to right through XOR operation, (2) for steganography, encrypted image has been altered by least significant bits (LSBs) of the cover image and obtained stego image, then (3) stego image has been watermarked in the time domain and frequency domain to ensure the ownership. The proposed approach is efficient, simpler and secured; it provides significant security against threats and attacks.

Information security is an important aspect of information. The importance of the value of information in every aspect can result in attempts to transfer access or theft of data and information by unauthorized parties. One technique for securing data and information is by applying the digital image steganography technique. Many methods can be used in steganography, some of which are Least Significant Bit (LSB), Pixel Value Differencing (PVD), and Modulus Function (MF). Good steganography must produce a stego-image with an image quality that is not different from the original image or what is called a cover image and has the storage capacity to store confidential data and is resistant to robustness. The purpose of this study was to compare the LSB, MF, and PVD methods to serve as alternatives to the use of steganography techniques. The results of this study indicate that the LSB method has the best image quality compared to the MF and PVD methods. For storage capacity, the PVD algorithm has a better capacity than the LSB and MF methods. Meanwhile, the robustness of the LSB, PVD, and MF methods has resistance to cropping with a percentage of 10% at the bottom of the stego-image.

Steganography algorithms used to secure sensitive data on the Internet. It hides the secret data in the cover image and provides imperceptibility to the attacker. The least significant bit (LSB) is the most preferred data hiding technique in the steganography. In this technique, the least significant bit of the cover image pixel replaced with data bits. In the literature, the data hiding achieved without considering the human visual system (HVS) characteristics that degrade the visual quality of the image. In this paper, the optimized data hiding has done while considering the HVS characteristics. The colour image contains three planes known as the red–green–blue plane. The green plane is the most sensitive, and blue is less sensitive to the human eyes. Thus, in the proposed technique, the green plane used as a reference plane for data hiding in the red and blue planes. In the optimized data hiding technique, the secret data bits match with the cover pixel bits. If the bits match, then the corresponding optimal index determines, else data hiding done in the LSB bits of the cover pixel. After that, the optimal indexes hide in the cover image using a 2-bit LSB technique. In the proposed technique, image smooth and edge region characteristics explored before data hiding. There is a high correlation between the consecutive pixels in the smooth region and the minimum correlation on the edges. Thus, we have matched the secret data bits with the cover pixel bits in the smooth region and hide the optimal indexes on the edges. The experimental results performed on the standard dataset images downloaded from the USC-SIPI image database. The experimental results show that the proposed technique provides better visual quality as compared to the existing techniques.

The general purpose of steganalysis algorithms is to detect a secret message in digital images. Nevertheless, previous studies have rather ignored the fact that more valuable information like message length can be extracted from stego images. In this article, a method is proposed for estimating message length in stego images resulted from PQ, which is a common steganography algorithm. In this method, the stego image resulted from PQ algorithm is first calibrated so that the corresponding cover image is obtained. Then, threshold μ is compared to the changes of global histograms of cover and stego images. If the threshold is less than the changes, first-order statistics and global histogram will be used to estimate message length; otherwise, secret message length will be estimated using second-order statistics and changes of variation of cover and stego images.

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 method of hiding confidential data in various medias like audio, image etc. Cryptography techniques are also integrated with steganography for data encryption. But in existing systems, poor encryption techniques are used which provide low security to data and this encrypted data is directly transmitted. So if there is any intruder in the network, can directly decrypt the data using the key. Thus there arises the need to enhance the existing system's security. To enhance the security, in this system the standard encryption method known as Advanced Encryption Security (AES), image split and random pixel embedding techniques are integrated before the data transmitted through the network. The data is encrypted in the system using AES and it is embedded in the least significant bit (LSB) of randomly selected pixels of image. After that the stego image is splitted into fragments on the basis of various intensity of RGB color component of pixel. Then the splitted parts are encrypted and transmitted to the receiver. So during the transmission, if there is any intruder in the network gets key and tries to decode the data, he only gets a portion of data. The sender informs the secret key to the receiver through email. The receiver extracts each image fragments and combined to form the stego image. Then the receiver decodes the secret data from the image. Thus the original image and secret data are received securely. The robustness of the system is evaluated through the histogram analysis and the system achieved target of improved imperceptibility with high PSNR of 60dB.

This paper presents a new secret sharing scheme for identification of cheaters in the elections. In a proposed scheme secret image (voter ID) is embedded into cover image (Indian emblem) of same size and generates n stego images. The resulting stego images are visually good and look like a cover image. Various image quality metrics are used to assess the quality of stego images. Out of n stego images only last two stego images are required to reconstruct the secret and cover images without any loss. The proposed scheme offers high embedding capacity. Experimental results of proposed scheme shown to be superior in terms of PSNR and visual quality than existing schemes.

This paper presents an image hiding method which embeds the secret image in the least significant bits (LSB) of the pixels selected from a cover image. Generally, LSB-related methods are rather sensitive to the modifications on the cover image. To abate the damage to the reconstructed cover image, this proposed method hence embeds the vital data of the cover image in more significant bits. This paper also provides a breadth first traversal (BFT) linear quadtree representation to characterize a compressed binary image. The data in the front of this structure are vital data; yet, those in the rear are the trivial ones. The strategy of this representation does facilitate image embedding.