Embed Secret Message Research Articles

Embedding Secret Data in Digital Media Using Texture Synthesis

A steganography is an art of hiding confidential data into digital media such as image, audio, video etc. Texture synthesis uses the concept of the patch which represents an image block of source texture where its size is user specified. A texture synthesis process resamples a smaller texture image and provides a new image with arbitrary size and shape. Instead of using an existing cover image to hide messages, the algorithm conceals the source texture image and embeds secret messages using the process of texture synthesis. This allows extracting the hidden messages and source texture from a stego synthetic texture. This offers the advantages like, First, it provides the embedding capacity that is proportional to the size of the stego texture image. Second, the reversible capability inherited from this includes functionality, which allows recovery of the source texture. And third, there will be no image distortion since the size of the new texture image is user specified.

Robust video steganography for social media sharing based on principal component analysis

Most social media channels are lossy where videos are transcoded to reduce transmission bandwidth or storage space, such as social networking sites and video sharing platforms. Video transcoding makes most video steganographic schemes unusable for hidden communication based on social media. This paper proposes robust video steganography against video transcoding to construct reliable hidden communication on social media channels. A new strategy based on principal component analysis is provided to select robust embedding regions. Besides, side information is generated to label these selected regions. Side information compression is designed to reduce the transmission bandwidth cost. Then, one luminance component and one chrominance component are joined to embed secret messages and side information, notifying the receiver of correct extraction positions. Video preprocessing is conducted to improve the applicability of our proposed method to various video transcoding mechanisms. Experimental results have shown that our proposed method provides stronger robustness against video transcoding than other methods and achieves satisfactory security performance against steganalysis. Compared with some existing methods, our proposed method is more robust and reliable to realize hidden communication over social media channels, such as YouTube and Vimeo.

SECURE TEXT IN IMAGE STEGANOGRAPHY USING PIXEL-BASED ALGORITHM

The art of encrypting a hidden message within a public message is known as steganography. Traditionally methods like LSB (least significant bit) modification, the five-modulus method and other algorithms have been utilized to encode a lower quality image into a higher resolution image via steganography. This research aims to implement a novel text in image steganography using pixel-based algorithms where the security of the text is enhanced by integrating encryption before embedding secret messages. We use the Chinese Remainder Algorithm (CRT) to cryptographically secure the secret message inside the image and the least significant bit algorithm to store the message inside the image. A novel method is propounded for the key generation of the CRT algorithm and the results have been studied and compared with the results of the methods in existing studies.

Constructive image steganography using example-based weighted color transfer

Image steganography aims to hide secret information without arousing suspicion that an image has conveyed hidden messages. The majority of image steganographic algorithms usually embed secret messages by altering pixels of a cover image. Despite achieving some degree of success, such a cover modification approach leads to certain telltale signs detected by steganalytic tools, thus unveiling the very existence of secret messages. In this paper, we propose a novel constructive steganographic algorithm to disguise the hidden information without involving a pre-existing cover image. Our WCTCIS scheme transforms secret messages into a stego image, taking advantage of example-based weighted color transfer, which synthesizes a new image with different colors by referring to a reference image. Our scheme first encodes secret message to increase the security using a modified two-dimensional lag-complex logistic map. An optimal weight is then derived using one of four measure techniques we suggest. Next, we conduct an example-based weighted color transfer to produce a temporary image, where each pixel is represented by a floating-point format. Finally, we conceal secret messages when synthesizing a pixel using a predetermined embedding vector. An intensive testing based on a database containing 5,000 natural images confirms that our algorithm offers a large payload and produces a stego image with significantly high quality. The CIEDE2000 color difference metric demonstrates that the stego image has high-fidelity color appearance. A security analysis shows that our scheme can resist current state-of-the-art learning-based ECMV steganalysis as well as statistic-based RS steganalysis, and is robust to salt-and-pepper noise attacks. The probability of breaking down our scheme is insignificantly small. The contribution of our work is introducing a constructive steganographic algorithm which makes use of color changes to conceal secret messages, produces better performance than the current state-of-the-art algorithms, and extends a color processing technique to achieve constructive steganography.

Carrier Image Rearrangement to Enhance the Security Level of LSB Method of Data Steganography

Least significant bit method is one of the most popular methods of data steganography, this method is very simple and provides good values for MSE and PSNR. LSB method is not secure enough and the embedded secret message can be easily hacked by any person with any programming experience. To enhance the security level of LSB and to protect the secret message from being hacked and addition stage is recommended. This stage adds a necessary protection without affecting the quality parameters and the efficiency of LSB. The protection process is based on using a complex private key, this key is generated by sender depending on the block size and the selected image size and kept in secret to be used by the receiver, the private key can be changed or updated any time, when the needs arise.

Modified Multiway Pixel-Value Differencing Methods Based on General Quantization Ranges for Image Steganography

A modified multiway pixel-value differencing method for image steganography using general quantization ranges of pixel pairs&#x2019; difference values is proposed, where the widths of the quantization ranges are not limited to be powers of two. The method can be employed to embed a secret message into a cover image with a higher embedding rate. The cover image is partitioned into non-overlapping complete or incomplete blocks using <inline-formula> <tex-math notation="LaTeX">$1 \times 3$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$2 \times 2$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$2 \times 3$ </tex-math></inline-formula>, or <inline-formula> <tex-math notation="LaTeX">$3 \times 3$ </tex-math></inline-formula> block templates. The message bitstream, whose bit positions are randomized in advance by use of a random number generator, can be embedded in the resulting blocks. More specifically, one pixel in each block is set as a shared pixel, and the least-significant-bit substitution method with the optimal pixel adjustment process is employed to embed message bits into the shared pixel. Next, the shared pixel in the block is combined with each remaining pixel to form a pixel pair, which is then utilized to embed message bits by a new pixel-value differencing method. Also, the use of non-power-of-two range widths is accomplished by a multiple-based number conversion mechanism, and the shared pixel in each block, as well as each related pixel pair whose two grayscale values pass a falling-off-boundary check, are used to embed the digits of the resulting multiple-based number. The experimental results show that the embedding rates yielded by the proposed method are higher than those yielded by existing multiway pixel-value differencing methods. The stego-images resulting from embedding secret messages retain good image quality, and the RS steganalysis process cannot detect the presence of the embedded secret messages.

High-Capacity Reversible Data Hiding in Encrypted 3d Mesh Models Based on Multi-Msb Prediction

As a new generation of digital media for covert transmission, three-dimension (3D) mesh models are frequently used and distributed on the network. Facing the huge massive of network data, it is urgent to study a method to protect and store this large amounts of data. In this paper, we proposed a high capacity reversible data hiding in encrypted 3D mesh models. This method divides the vertices of all 3D mesh into embedded sets and sets based on the parity of the index. In addition, the multiple most significant bit (Multi-MSB) prediction reserved space is used to adaptively embed secret message, and the auxiliary information is compressed by arithmetic coding to further free up redundant space of the 3D mesh models. We use the majority voting system(MSV) principle to restore the original mesh model with high quality. The experimental results show that our method achieves a higher embedding capacity compared with state-of-the-art RDH-ED methods on 3D mesh models and can restore the original 3D mesh models with high quality.

Crypto-Steganographic Method to Protect Secret Messages

Multiple methods are used to hide secret messages in digital color images, and the most important and most common is the least significant bit (LSB) method. The LSB method is a known and exposed method, and anyone with programming experience can retrieve the secret message embedded in the digital image. In this paper research we will add some enhancements to improve the security level of LSB method to protect the embedded secret message from being hacked. A simple method of secret message cryptography will be used to encrypt the secret message before bedding it using LSB method. The method will be based on using color image as an image_key; this image_key will be resized to generate the needed secret private key used to encrypt-decrypt secret message. The length and the contents of the generated private key will dynamically change depending on the message length and the selected image_key. The selected image_key will be kept in secret without transmission and will be known only by the sender and receiver and it can be changed any time when needed. The proposed crypto_steganographic method will be implemented to show how it will increase the level o secret message protection.

Secure Data Transmission Based on Adaptive Chattering-Free Sliding Mode Synchronization of Unified Chaotic Systems

This paper is concerned with a novel secure data transmission design based on adaptive synchronization of master and slave unified chaotic systems. First, by introducing an augmented error state, an adaptive continuous sliding mode control (SMC) is derived to guarantee the synchronization of unified chaotic systems. Then, the secret message embedded in the master chaotic system can be transmitted from transmitter to receiver. Different from previous works using discontinuous SMC, the undesired chattering phenomenon can be fully eliminated, and it becomes possible to precisely recover the embedded secret message at the receiver. Last, an example is given to illustrate the success of secure data transmission with the continuous SMC developed in this paper.

Multiple Image Based Dual Steganography Using Arnold Transform and Block Code Encoding

Security plays a crucial role in the field of Social media network. Securing the data become one among the largest challenges in the present scenario. Whenever we expect concerning the cyber security, the primary issue that involves our mind is ‘cyber crimes’ that are increasing vastly day by day. Embedding secret message into the image (Steganography) is associated with art and science of secure data communication wherever the key information or confidential information is hidden in host file. It's employed incompletely different helpful applications like secure electronic communication, health care and military. Confidential information’s are unremarkably keep in digital media and transmitted via network cause of rapid growth of internet. In this paper, steganography techniques which might be used to safeguard the information from intruders. Here, Steganographic technique is used to hide multiple secret images into a single 24-bit cover image using Least Significant Bit (LSB) and dual steganography method. Multiple secret images are scrambled and encoded before hiding into cover image using Arnold Transform and Block Code Encoding. The Proposed technique is Block Code Encoding to convert Secret message to binary and bit pairs to form safer information. The main goals of proposed work offers security and high limit based steganography plan of concealing a massive size secret image into a bit size cover image, to enhance security using dual steganography, image quality and to reduce error.

Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

Data Hiding Based on Mini Program Code

A mini program code (also known as sunflower code) comes with WeChat mini program APPs. With the popularization of mini program APPs, mini program codes have become more and more widely used. As a new carrier, the study of information hiding technology based on mini program code is of great significance for the expansion of covert communication carriers and can also deal with security problems in advance. At present, to the best of our knowledge, there is no steganographic research based on mini program codes. In this paper, we propose a scheme to embed secret information into mini program codes for the first time. After studying the construction of mini program codes, a coordinate system is constructed to represent its module coordinates. Then, a binary stream of the secret message is embedded into the encoding region or the edge patch. Experiments show that the proposed data hiding scheme is effective and feasible. The embedded secret message could be extracted while keeping the readability of the mini program code. Moreover, the secret payloads of the encoding region and the edge patch for the V-36 mini program code are 72 bits and 29 bits, respectively.

An improved separable reversible patient data hiding algorithm for E-healthcare

In the telemedicine industry, a standout among the most significant issue is the exchange of Electronic Patient Information (EPI) between patient and a doctor that are remotely connected. A minute change to EPI may result in a wrong diagnosis for the patient. To ensure secure and safe communication for telemedicine applications, a dual-image separable block-based reversible data hiding algorithm in encrypted domain for embedding secret message in base5 numeral framework is proposed here. The proposed scheme has not been suffering from underflow and overflow problem so that empowering it to embed and recover information precisely from low-intensity pixels too. This property makes our proposed methodology truly reasonable for its utilization on medical images. To prove the effectiveness of our proposed approach, experiments have been performed on different test images. The average PSNR value is 54.10 dB for an embedding capacity of 327,680 bits for all test images which demonstrates that the method is capable of giving good quality stego images even at high payload also. The experimental study revealed that for all types of test images, the proposed methodology altogether beaten all the compared methodologies in its ability to embed secret message and precisely recover it by maintaining the visual quality of stego images too.

A high payload reversible data hiding algorithm for homomorphic encrypted absolute moment block truncation coding compressed images

With the aim to ensure privacy and security of secret message, an enhanced reversible data hiding algorithm in encrypted as well as compressed domain is proposed here. After compression of grey-scale image using absolute moment block truncation coding (AMBTC) method, pixels of AMBTC compressed image is segmented into two types - seed pixels (2k…255) and remaining pixels are called non-seed pixels. Now, embedded k, (k ≥ 1) binary bits of secret message by changed over it into base10 numeral framework at seed pixels of AMBTC compressed image whereas seed pixel is divided into two individual units which are encrypted through Paillier cryptosytem separately. Highlight of proposed method is to embed variable size secret message at seed pixels of AMBTC compressed image without any occurrence of overflow problem. Experimental study revealed that for all type of test images, proposed method altogether beated all the compared methods in its ability to embed secret message and precisely recover it with a PSNR value of $\infty $ dB between cover image and reconstructed image too.

An efficient DCT-SBPM based video steganography in compressed domain

In this research work, an efficient robust video steganography in compressed domain is presented based on discrete cosine transform (DCT) encoded with H.264 codec. In this method, a compressed video (.mp4) of different resolutions, frame rates and sizes are used as a cover and RGB image is used as a secret message. Using appropriate stego key, the secret frames from the sequence of video frames are selected and the non-dynamic pixels of these frames are identified. The least significant bits (LSB) of the DCT component of these non-dynamic pixels are used as carrier object for hiding the R, G, and B components of secret message individually. An appropriate embedding key is designed to embed secret message in cover video such that the quality assessment parameters viz. Peak signal-to-noise ratio (PSNR) and mean square error (MSE) of imperceptibility can be optimized. Also, the successful extraction of secret message from the cover stego video is assessed by the robustness parameters viz. Bit error rate (BER) and similarity (Sim). The hiding capacity of proposed video steganography with respect to secret message and cover frame is measured by using hiding ratio (HR). The efficiency of proposed video steganography method is compared with the reported methodologies on the basis of the parameters of imperceptibility and robustness.

Retracing extended sudoku matrix for high-capacity image steganography

Numerous data hiding algorithms have been devised for imperceptibly embedding secret messages into the cover media so as to securely transmit user privacy information over the public communication channels. Among them, the reference matrix-based schemes in spatial domain draw extensive concern on account of the simple but efficient embedding and extraction procedure. The core idea of the planar matrix-based method is let two contiguous cover pixels conceal a base-N secret digit with the guidance of reference matrix, such as Sudoku, Turtle Shell, and so on. A novel image data hiding scheme with great embedding efficiency is presented in this paper, which is based on retracing extended Sudoku (RE-Sudoku) reference matrix. Owing to the number of Sudoku solutions and various extension directions, viz., the multiformity of RE-Sudoku matrix, this scheme is exceedingly more secure than the previous methods. More momentously, the proposed two-dimensional reference matrix can guide two 9-ary notational system secret digits to be embedded into each cover pixel pair simultaneously; thereby resulting in a larger embedding rate which converges to 3.169 bits per pixel. The experimental results reveal that this image steganography outperforms the other related works in terms of hiding capacity while maintaining a desirable image quality around 40 dB. Furthermore, the security of our proposed scheme is verified by demonstrating its resistance to the pixel-value difference histogram (PDH) and regular/singular (RS) steganalysis.

Coverless Image Steganography Based on Optical Mark Recognition and Machine Learning

The most significant factor to consider during private information transmission through the internet (i.e., insecure channel) is security. So, to keep this data from unauthorized access during transmission, steganography is used. Steganography is the scheme of securing sensitive information by concealing it within carriers such as digital images, videos, audio, text, etc. Current image steganography methods work as follows; it assigns cover image then embeds the secret message within it by pixels' modifications, creating the resultant stego-image. These modifications allow steganalysis algorithms to detect the embedded secret message. So, a coverless data hiding concept is proposed to solve this problem. Coverless does not mean that the secret message will be transmitted without using a cover file, or the cover file can be discarded. Instead, the secret message will be embedded by generating a cover file or a secret message mapping. In this paper, a novel, highly robust coverless image steganography method based on optical mark recognition (OMR) and rule-based machine learning (RBML) is proposed.

A Video Steganography Method Based on Transform Block Decision for H.265/HEVC

High definition video application has drawn a lot of interest both from academy and industry. The relevant latest video coding technology, H.265/HEVC has been a promising area for video steganography. In this paper, we present a novel and efficient video steganography method based on transform block decision for H.265. In order to improve the visual quality of carrier video, we analyze the embedding error of data hiding with modifying partitioning parameters of CB, PB and TB, and modify the transform block decision to embed secret message and update corresponding residuals synchronously. In order to limit embedding error, we utilize an efficient embedding mapping rule which can embed N (N>1) bits message and at most modify one bit transform partitioning flag. Our experimental results show that the proposed method can achieve better visual quality, larger embedding capacity and less bit-rate increase than state-of-the-art researches.

A New Adversarial Embedding Method for Enhancing Image Steganography

Image steganography aims to embed secret messages into cover images in an imperceptible manner. While steganalysis tries to identify stegos from covers, which is a special binary classification problem. Recently, some literatures show that the adversarial embedding can mislead the advanced steganalyzers based on convolutional neural network (CNN), and thus enhance the steganography security. Since adding perturbations to stegos may lead to messages extraction failure due to properties of syndrome-trellis codes (STC), the existing adversarial examples are derived from covers or their enhanced versions, while those stegos are not fully utilized. In this paper, we propose a new adversarial embedding scheme for image steganography. Unlike those related works, we first combine multiple gradients of cover and generated stegos to determine the directions of cost modifications. Next, instead of adjusting all or a random part of embedding costs in existing works, we carefully select the candidate costs according to the amplitudes of cover gradients and their costs. Extensive experimental results demonstrate that by adjusting a tiny part of embedding costs (less than 5% in most cases), the proposed method can significantly improve the security of five modern steganographic methods evaluated on both re-trained CNN-based and traditional steganalyzers, and achieve much better security performances compared with related methods. In addition, the security performances evaluated on different image database show that the generalization of the proposed method is good.

An encrypted coverless information hiding method based on generative models

Invisibility is an important target for image steganography; however, the traditional image steganography methods inevitably leave traces of their modifications in cover images due to the process used to embed secret messages. In this paper, we propose an encrypted coverless information hiding method that transfers secret images between two different image domains using generative models. Our method includes two stages: encryption and decryption. In the encryption stage, we first embed a secret image into a public image (one domain) to obtain a synthetic image; then, we utilize that image as the input to the first generative model F to obtain an encrypted image (another domain). Adversarial loss and an extraction module are added to improve the quality of the encrypted images generated in this stage. In the decryption stage, we design a second generative model G to reconstruct the synthetic images from the encrypted images. Finally, the secret image is separated from the reconstructed synthetic image. In our extensive experiments, we adopt the images in the MNIST dataset as the secret images, which allows us to use the recognition rate as a measure of the secret image reconstruction quality. The experimental results indicate that our method is not only able to generate quality encrypted images compared with current popular image-to-image translation methods but also possesses greater security, robustness and reconstruction ability.