Secret Data Bits Research Articles

A secure image steganography based on LSB technique and 2D chaotic maps

This paper introduces a pioneering, effective data-hiding algorithm using different sizes of cover images and different types of secret data (image, txt, and audio). The proposed algorithm is based on a hybrid 1D chaotic map combined with a 2D composite chaotic map paired with optimization and Least Significant Bits (LSB) techniques. We employ chaotic maps to create the initial embedding position vector, and LSB to hide the secret message in the cover image. The optimization technique utilizes the chaotic maps to optimize the random embedding sites, looking for value matches between the cover image pixels and the secret data bits. This partial improvement leads to a high-quality stego-image, a large embedding capacity, imperceptibility to the human eye, undetectability, and enhanced security. The outcomes of the extensive experiments show that when the payload is 4.2 bits per pixel, the peak signal-to-noise ratio value (PSNR), which expresses the visual quality, is above 30 dB. Furthermore, the experimental results illustrate that the system exhibits robustness against various types of attacks. As a final point of strength, the large key space (2^206) prevents the secret data from being resolved if stego-images are accessed by intruders or third parties. Even minor changes in key bits can significantly alter the extracted secret data, resulting in entirely different secret data.

A Mellin transform based video steganography with improved resistance to deep learning steganalysis for next generation networks

In the era of 5 G network advancements, the potential for extremely robust, less-latency, and huge-capacity communication opens up new perspective for multimedia. Steganography enables embedding of sensitive data within multimedia files, making it unreadable to unauthorized third parties. Notably, when using videos as cover, the capacity for data embedding is substantially increased. Recent developments in steganography have largely revolved around modified versions of transform domain techniques. Due to this repetitiveness, it becomes easier for steganalytic tools in detecting concealed data. Addressing this issue, our paper introduces an innovative data embedding approach MARVIS based on the Mellin transform. The superiority of the proposed approach is exhibited using the metrics, MSE, PSNR, and SSIM. MARVIS has achieved PSNR of 50–60 dB and SSIM of 0.9998 for embedding 4 bits of secret data, outperforming other methods that achieve 40 dB for 1 bit. By quadrupling stego capacity, we can embed more secret data per pixel without compromising the integrity of the cover object.•MARVIS utilizes phase modulation for data embedding, offering advantages beyond traditional frequency domain techniques which use frequency domain for data embedding.•The effectiveness of the proposed data embedding approach is validated through Y-Net, a deep learning-based steganalysis tool.

Privacy‐preserving in the smart healthcare system using steganography and chaotic functions based on DNA

AbstractThe smart healthcare system is one of the Internet of Things‐based applications that are increasingly used nowadays. One of the requirements of this system is privacy‐preserving, which should protect the disclosure of the patient record contents. In the present paper, a combination of chaotic functions and a new DNA‐based steganography method, and image blocking are suggested to protect patients' privacy‐preserving. First, the image is blocked, and the initial key for the chaotic function will be gained by using the centers of the blocks. Then the data and image are transformed into DNA sequences. Finally, one of the randomly chosen DNA strands of data is XOR with the center of one randomly selected block and will be placed in one of the block pixels. The failure to send the initial key separately to generate random numbers, as well as the random selection of secret data bits and image pixels for steganography has increased the security of the proposed method. The simulation results not only indicate the quality of the stego‐image but also show better performance of the proposed method than the existing methods.

High Payload Lossless Steganography Using Image Interpolation

Interpolation-based reversible data hiding (IRDH) is a method for embedding data in a reversible manner into digital images. It is based on the polynomial interpolation to hide the secret data bit stream in the coefficients of the interpolation polynomial. In this paper, an IRDH method that combines a modified neighbor mean interpolation is presented with a new method for reversibly embedding secret data in interpolated pixels. This method uses log base 2 of the decimal value of the interpolated pixel to replace a corresponding number of bits with the bits of the secret data, allowing for a higher bit stream to be embedded with better image quality. The results from experiments show that the introduced method can implant on average, 1300000 bits of secret data with an average PSNR of 28.5 dB, which is a significant improvement over existing and related works.

A Multistage High Capacity Reversible Data Hiding Technique Without Overhead Communication

Reversible Data Hiding(RDH) has been extensively investigated, recently, due to its numerous applications in the field of defence, medical, law enforcement and image authentication. However, most of RDH techniques suffer from low secret data hiding capacity and communication overhead. For this, multistage high-capacity reversible data hiding technique without overhead is proposed in this manuscript. Proposed reversible data hiding approach exploits histogram peaks for embedding the secret data along with overhead bits both in plain and encrypted domain. First, marked image is obtained by embedding secret data in the plain domain which is further processed using affine cipher maintaining correlation among the pixels. In second stage, overhead bits are embedded in the encrypted marked image. High embedding capacity is achieved through exploiting histogram peak for embedding multiple bits of secret data. Proposed approach is experimentally validated on different datasets and results are compared with the state-of-the-art techniques over different images.

Reversible Data Hiding Using an Improved Pixel Value Ordering and Complementary Strategy

Reversible data hiding (RDH) schemes based on pixel value ordering have gained significant popularity due to their unique capability of providing high-quality marked images with a decent embedding capacity, while also enabling secret information extraction and the lossless recovery of the original images at the receiving side. However, the marked image quality may be distorted severely when the pixel value ordering (PVO) method is employed in a layer-wise manner to increase the embedding capacity. In this paper, a new high-capacity RDH scheme using a complementary strategy is introduced to overcome the limitation of the image quality in the case of layer-wise embedding. The proposed RDH scheme first divides the cover image into non-overlapping blocks of 2 × 2 pixels uniformly and then sorts the pixels of each block according to their intensity values. The secret data are then embedded into two layers. In the first layer, the minimum value of the block is decreased and the maximum value is increased by either 1 or 2 to embed the secret data bits. The second layer is used as a complement to the first layer and is in symmetry with the first layer. In the second layer, the proposed RDH scheme increases the minimum valued pixel and decreases the maximum valued pixel in order to minimize the distortion resulting from the first layer embedding and to embed an additional amount of the secret data. As a result, the proposed RDH scheme significantly increases the embedding capacity, which is clearly evident from the conducted experimental results.

Secure Reversible Data Hiding in Images Based on Linear Prediction and Bit-Plane Slicing

Reversible Data Hiding (RDH) should be secured as per requirements to protect content in open environments such as the cloud and internet. Integrity and undetectability of steganographic images are amongst the main concerns in any RDH scheme. As steganographic encryption using linear prediction over bit-planes is challenging, so the security and embedding capacity of the existing RDH techniques could not be adequate. Therefore, a new steganographic technique is proposed which provides better security, higher embedding capacity and visual quality to the RDH scheme. In this technique, the cover image is divided into n-bit planes (nBPs) and linear prediction is applied to it. Next, the histogram of the residual nBPs image is taken, and secret data bits are encrypted using the RC4 cryptographic algorithm. To embed the encrypted secret data bits, the histogram shifting process is applied. This is achieved by using peak and zero pairs of residual nBPs images. This scheme provides security to the cover image and hidden data. The proposed RDH scheme is capable of extracting the embedded secret data accurately and recovering the original cover or residual nBPs image.

Privacy-preserving in the Internet of Things based on steganography and chaotic functions

Nowadays, with the spread of the Internet and its applications, the use of the Internet of Things is becoming increasingly widespread. One of the requirements of the Internet of Things is privacy-preserving, which protects the personal and confidential information of individuals. In this paper, to preserve the privacy of personal and confidential information, a combination of chaos functions and a new steganography method based on image blocking is proposed. In this paper, block centers are used to generate the initial key of the chaos function, then randomly selected secret data bits are hidden in the pixels of randomly selected blocks. The simulation results not only show the quality of the stego_image but also the better performance of the proposed method compared to the existing methods.

An adaptive high capacity reversible data hiding algorithm in interpolation domain

Reversible data hiding (RDH) algorithms using interpolation technology have the advantage of high capacity for single-layer embedding. However, existing algorithms usually embed secret data in the non-reference pixels based on simple additions without considering the properties of context-pixels, which results in that the visual quality of watermarked image is not optimal. To deal with this issue, a novel adaptive high capacity RDH algorithm is proposed. Firstly, a location-dependent weighted image interpolation method is proposed to improve the visual quality of the interpolated image. Then, the interpolated image is divided into overlapping blocks, which are sorted in an ascending order according to their standard deviations; secret data is preferentially embedded in the blocks with small deviation so that image quality is not distorted too much. Finally, to enhance embedding capacity as much as possible, the amount of secret data bits that can be embedded in non-reference pixels is calculated adaptively. We theoretically prove that the embedded secret data can be extracted correctly and there is no pixel overflow or underflow problem. Extensive experimental results showed that the proposed algorithm outperforms several state-of-the-art algorithms. In addition, our algorithm can resist steganalysis attacks, and demonstrated the effectiveness of the proposed algorithm.

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Ransomware is considered one of the most threatening cyberattacks. Existing solutions have focused mainly on discriminating ransomware by analyzing the apps themselves, but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then analyzed. Therefore, this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding (HEVC) steganography approach. The main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different blocks. After that, the Least Significant Bit (LSB) based Hamming Distance (HD) calculation is performed amongst the secret data’s divided blocks and cover frames. Finally, the secret data bits are hidden into the marked bits of the cover HEVC frame-blocks based on the calculated HD value. The main advantage of the suggested steganography approach is the minor impact on the cover HEVC frames after embedding the ransomware while preserving the histogram attributes of the cover video frame with a high imperceptibility. This is due to the utilization of an adaptive steganography cost function during the embedding process. The proposed ransomware hiding approach was heavily examined using subjective and objective tests and applying different HEVC streams with diverse resolutions and different secret ransomware apps of various sizes. The obtained results prove the efficiency of the proposed steganography approach by achieving high capacity and successful embedding process while ensuring the hidden ransomware’s undetectability within the video frames. For example, in terms of embedding quality, the proposed model achieved a high peak signal-to-noise ratio that reached 59.3 dB and a low mean-square-error of 0.07 for the examined HEVC streams. Also, out of 65 antivirus engines, no engine could detect the existence of the embedded ransomware app.

Data Hiding in AMBTC Images Using Selective XOR Hiding Scheme

Nowadays since the Internet is ubiquitous, the frequency of data transfer through the public network is increasing. Hiding secure data in these transmitted data has emerged broad security issue, such as authentication and copyright protection. On the other hand, considering the transmission efficiency issue, image transmission usually involves image compression in Internet-based applications. To address both issues, this paper presents a data hiding scheme for the image compression method called absolute moment block truncation coding (AMBTC). First, an image is divided into non-overlapping blocks through AMBTC compression, the blocks are classified four types, namely smooth, semi-smooth, semi-complex, and complex. The secret data are embedded into the smooth blocks by using a simple replacement strategy. The proposed method respectively embeds nine bits (and five bits) of secret data into the bitmap of the semi-smooth blocks (and semi-complex blocks) through the exclusive-or (XOR) operation. The secret data are embedded into the complex blocks by using a hidden function. After the embedding phase, the direct binary search (DBS) method is performed to improve the image quality without damaging the secret data. The experimental results demonstrate that the proposed method yields higher quality and hiding capacity than other reference methods.

A Multiplicative-Additive Chaotic-Address Steganography

In this study, Multiple-Chaotic maps were merged by using multiplicative-additive form to generate the
 chaotic sequences which are used to track the addresses of shuffled bits in steganography. Three techniques are
 introduced for image steganography in the spatial domain. The first system is based on the well-known LSB
 technique, the second system is based on looking for the identical bits between the secret message and the cover
 image and the third system is based on the concept of LSB substitution, it is employed the mapping of secret data bits
 with cover pixel bits. It was tested and evaluated security levels for the proposed techniques by using the Peak
 Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), histogram analysis and correlative analysis and tested the
 Chaotic sequences generated by using correlation, Lypaunov exponents, Poincaré section and 0-1Test. The results
 show that the proposed methods perform better than existed systems.

High-Capacity and High-Quality Reversible Data Hiding Method Using Recurrent Round-Trip Embedding Strategy in the Quotient Image

In previous research, scholars always think about how to improve the information hiding algorithm and strive to have the largest embedding capacity and better image quality, restoring the original image. This research mainly proposes a new robust and reversible information hiding method, recurrent robust reversible data hiding (triple-RDH), with a recurrent round-trip embedding strategy. We embed the secret message in a quotient image to increase the image robustness. The pixel value is split into two parts, HiSB and LoSB. A recurrent round-trip embedding strategy (referred to as double R-TES) is designed to adjust the predictor and the recursive parameter values, so the pixel value carrying the secret data bits can be first shifted to the right and then shifted to the left, resulting in pixel invariance, so the embedding capacity can be effectively increased repeatedly. Experimental results show that the proposed triple-RDH method can effectively increase the embedding capacity up to 310,732 bits and maintain a certain level of image quality. Compared with the existing pixel error expansion (PEE) methods, the triple-RDH method not only has a high capacity but also has robustness for image processing against unintentional attacks. It can also be used for capacity and image quality according to the needs of the application, performing adjustable embedding.

Novel Secure Hybrid Image Steganography Technique Based on Pattern Matching

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

Highly imperceptible data hiding technique using MSB in the grayscale image

Security of confidential information during communication in the network has been the primary concern. Therefore, data hiding techniques have become the focal point among the researchers. In this regard, to keep the communication secret, watermarking and steganography are the two most important fields of data concealing. Image steganography techniques embed the secret data bits in the image's pixels to detour attention of outsiders. In this paper, an improved data hiding technique is proposed using the XOR features of the cover image (CI) pixels to conceal the secret data bits in the least significant bit (LSB). During embedding, the most significant bits (MSBs) of the pixels are partitioned into two different segments. Next, using these segments and the embedding bits, the stego-image pixels are obtained. The comparative analysis is done with various image steganography techniques to demonstrate that the proposed work offers better imperceptibility and capacity.

Dual-JPEG-image reversible data hiding

Because of the widespread popularity of JPEG image compression format, reversible data hiding (RDH) for JPEG images has practical application value with increasing research attention. This paper proposes a dual-image RDH method based on a modification of the discrete cosine transform (DCT) coefficients. Because of the limited embedding capacity, a dual-image strategy is introduced and improved according to the characteristics of JPEG. In our method, all nonzero DCT coefficients are embedded without the additional distortion caused by invalid modifications, and the spatial distortion caused by the modification of DCT coefficients with different frequencies varies. A dynamic allocation method is proposed to arrange the embedding capacity reasonably to achieve less distortion. The nonzero DCT coefficients can be embedded flexibly with different bits of secret data to significantly improve the embedding capacity. As far as we know, this is the first work to achieve RDH in JPEG images in a dual-image manner. Furthermore, we also apply the proposed method to the reversible authentication of JPEG images. Experimental results demonstrate the efficacy of the proposed method with high embedding capacity and satisfactory visual quality while suppressing file size expansion.

A Novel Image Steganography Method for Industrial Internet of Things Security

The rapid development of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) brings new security threats by exposing secret and private data. Thus, information security has become a major concern in the communication environment of IIoT and AI, where security and privacy must be ensured for the messages between a sender and the intended recipient. In this article, we propose a method called Harris hawks optimization-integer wavelet transform (HHO-IWT) for covert communication and secure data in the IIoT environment based on digital image steganography. The method embeds secret data in the cover images using a metaheuristic optimization algorithm called HHO to efficiently select image pixels that can be used to hide bits of secret data within integer wavelet transforms. The HHO-based pixel selection operation uses an objective function evaluation depending on the following two phases: exploitation and exploration. The objective function is employed to determine an optimal encoding vector to transform secret data into an encoded form generated by the HHO algorithm. Several experiments are conducted to validate the performance of the proposed method with respect to visual quality, payload capacity, and security against attacks. The obtained results reveal that the HHO-IWT method achieves higher levels of security than the state-of-the-art methods and that it resists various forms of steganalysis. Thus, utilizing this approach can keep unauthorized individuals away from the transmitted information and solve some security challenges in the IIoT.

Two-point FFT-based high capacity image steganography using calendar based message encoding

In this work, we show how to hide a maximum of 8 bits of secret data into the pixel difference value. Adjacent pixel pairs are chosen in a non-sequential manner in the spatial domain without using any seed or key. In spite of having high average embedding capacity and embedding efficiency, our algorithm can withstand visual, structural and statistical attacks. We compare our work with state-of-the-art works and also show that our work is capable of resisting the series of tests provided by the benchmark “StirMark”.

Image steganography based on Kirsch edge detection

Conventional steganography methods fabricate the secret information into the cover pixels without analyzing the pixel intensities of an image. As a result, some minor pixel level manipulations may lead to huge visual distortion in the stego-image. To this end, in this paper, a novel steganographic scheme based on Kirsch edge detector is proposed. The aim of the scheme is to maximize the payload by embedding more secret bits into edge pixels and fewer bits into the non-edge pixels. The proposed scheme has three major phases: construction of edge image, embedding and extraction. The first phase deals with the construction of masked image from the cover image, and in turn, edge image from the masked one. The second phase deals with the decomposition of the cover image into a set of triplet of pixels and then embedding of (x + y + 1) bits of secret data into each triplet of pixels to obtain the stego-image. Here, ‘x’ and ‘y’ are not fixed as the edge information of each triplet changes incessantly. The third or last phase deals with the extraction of the secret information from the stego-image using the reverse process. Simulation results on some standard images ensure that the proposed method achieves higher payload and better image quality compared to the conventional steganographic schemes. Furthermore, the Kirsch edge detector is able to produce more number of edge pixels compared to the traditional edge detectors; and, hence the proposed scheme also outperforms the existing edge-based methods in terms of payload.

Coverless VoIP Steganography Using Hash and Hash

Abstract Performing secure and robust embedding and extracting in real time voice streams without deteriorating the voice quality is a great challenge. This paper aims on hiding the secret data bits in the voice packets without modifying any data in the cover thereby improving the embedding transparency and becomes robust against the steganalysis attacks using coverless approach. Initially a hash array is built with the frame size. The cover bit position is identified from the hashing function. The hash array is marked with a flag value to indicate that the particular sample consist of the secret message bit. The hash array is attached with the VoIP samples, at the receiver side the hash table is separated, and the secret bits are extracted based on the hash array. The experimental results conducted on a VoIP prototype proved to be simpler and effective in terms of the computational complexity, undetectability and voice quality at both sender and receiver end.