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Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.

Line codes are widely used to protect data transmission and storage systems against errors, keep various cryptographic algorithms and protocols working stably, and protect hidden information from errors in a stegocontainer. One of the code classes applied in a number of the listed areas is linear self-complementary codes over a binary field. These codes contain a vector of all ones and their weight numerator is a symmetric polynomial. In applied problems, self-complementary [n, k] codes are often required to have the maximal possible code distance d(k, n) at given length n and size k. The values of d(k, n) are already known for n < 13. The task formulated in this paper for self-complementary codes with length n = 13, 14, 15 is to find lower estimates of d(k, n) and values proper of d(k, n). The development of an efficient method for obtaining a lower estimate close to d(k, n) is an urgent task, because finding values proper of d(k, n) is generally a difficult task. The paper proposes four methods for finding lower estimates. These methods are based on cyclic codes, residual codes, the (u|u + v) structure, and the tensor product of codes. The methods are used together for the considered lengths to efficiently obtain lower estimates which either coincide with found values of d(k, n) or differ from them by one. The paper proposes a sequence of checks, which in some cases helps prove the absence of a self-complementary [n, k] code with code distance d. The final part of the work proposes an information hiding structure based on self-complementary codes. This structure is resistant to interference in the stegocontainer. The calculations show that the new structure is more efficient when compared with the known counterparts. [ABSTRACT FROM AUTHOR]

The design and development of secure nonlinear cryptographic Boolean function plays an unavoidable measure for modern information confidentiality schemes. This ensure the importance and applicability of nonlinear cryptographic Boolean functions. The current communication is about to suggest an innovative and energy efficient lightweight nonlinear multivalued cryptographic Boolean function of modern block ciphers. The proposed nonlinear confusion element is used in image encryption of secret images and information hiding techniques. We have suggested a robust LSB steganography structure for the secret hiding in the cover image. The suggested approach provides an effective and efficient storage security mechanism for digital image protection. The technique is evaluated against various cryptographic analyses which authenticated our proposed mechanism. [ABSTRACT FROM AUTHOR]

The idea of coverless information hiding has seen a great deal of development since it was initially introduced due to its effectiveness in defeating steganalysis tools. However, the capacity for general coverless information hiding methods to conceal information is limited, as well as no previous methods worked at the other requirements such as robustness. In this paper, a coverless image steganography (CIS) method for increasing capacity is proposed while retaining the robustness. The proposed method consists of several steps. Firstly, the secret data is segmented into segments of the n length. Secondly, a suitable image that has features similar to the secret message is selected and divided into non-overlapping blocks. Thirdly, these blocks are transformed into the frequency domain by applying discreet wavelet transform (DWT). Fourthly, building a hash sequence table using a suggested hashing algorithm. Fifthly, to reduce search time an indexing table is built based on the generated hash sequence. Sixthly, match each segment with the generated hash sequences and save the auxiliary information for each matched segment in the image in a file. Lastly, send the stego image and the auxiliary information file to the receiver. The experimental results show that the CIS method produces high capacity compared with previous CIS methods. [ABSTRACT FROM AUTHOR]

The deployment of biometrics spans over almost every application that incorporates user authentication. Fingerprint biometrics in particular is by far the most popular choice in biometric authentication systems. However, vulnerabilities such as database compromise, fingerprint reconstruction, and identity fraud have made it crucial to develop highly robust and privacy-preserving authentication systems. Although there have been considerable efforts in the area, security gaps such as dependency on singular point, scale variability and low user recognition performance limit the real-time application of these techniques. In this paper, we address these performance issues and put forth a novel technique for fingerprint template security. The secure templates generated by the proposed technique are computed using many-to-one mapped fully quantized features. A set of rotation and translation independent features are derived using minutiae triplets which makes the proposed secure fingerprint template an alignment-free user template. Each feature type is rotation and translation invariant making the templates free for scale anomalies. The technique essentially hides the true feature information of a fingerprint with the help of a non-invertible transformation function. This enables user identity verification in the transformed domain itself. An extensive result analysis using five fingerprint databases obtained from FVC2002 and FVC2004 has been carried out. The proposed technique delivers a superior performance compared to other noteworthy contributions and therefore proves to be fit for use in various applications involving fingerprint-based identity verification mechanisms. [ABSTRACT FROM AUTHOR]

This work deals with digital image processing using the steganography technique in real life. Various steganography techniques face data authentication, data security, and copyright issues. Due to the fact that the problem of data security is currently very topical, these techniques are often sought after. This is related to the constant development of new algorithms that provide solutions that will safely hide the secret message in the image and at the same time will be resistant to various types of attacks. The motivation for writing this work lies in the technique of representing a secret message using a Quick Response code. Later in this work is comparison between our results and results of approach made by scientific community, which works with data hiding within steganographic principles. The secret message is written in the least significant bit plane of the cover image, which ensures that the modification of the image cannot be detected by the naked eye. The proposed solution is evaluated by mathematical quality assessment parameters Peak signal-to-noise ratio, Mean squared error, Normalized cross-correlation and Structural similarity index. [ABSTRACT FROM AUTHOR]

In this era of information security and communication, a major priority is the achievement of a robust and secure steganography system when thinking about information concealment. The development of such an information-hiding scheme demands that the scheme be able to hide a secret message within the cover media. The most vexing issues in existing steganography protocols are imperceptibility, security, and capacity, and researchers have frequently emphasized a trade-off between these issues. Scholars have consistently ignored the balance between security and payload because resolving one problem has been shown to have an impact on the other, and vice versa. To overcome these problems, an effective method known as the Conventional Neural Network based Edge Detection Method (CNN-EDM) has been presented for image steganography in this study. The CNN-EDM is used to improve the contributions of the proposed scheme. Four main stages were used to achieve the objectives in this research, beginning with the cover image and secret image preparation, followed by embedding, and culminating in extraction. The last stage is the evaluation stage, which employs several evaluations to benchmark the obtained results. A standard database from the Signal and Image Processing Institute (SIPI) containing color and grayscale images with 512 × 512 pixels was utilized in this study. Different parameters were used to test the performance of the suggested scheme based on security and imperceptibility (image quality). The image quality was evaluated using three important metrics: histogram analysis, peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM). Furthermore, two metrics were used to evaluate the security properties of the proposed system: the Human Visual System (HVS) and Chi-square (X2) attacks. The evaluations showed that the proposed scheme can enhance the capacity, invisibility, and security features and address the already existing problems in this domain. [ABSTRACT FROM AUTHOR]

In today's digital age, security and safe communication are necessities. Applications frequently transport large amounts of private data as binary images. This research proposes a unique scheme that uses a cover pattern histogram-based decision tree for information concealment and extraction from binary images. This research aims to provide a data-hiding approach with a large capacity for data concealment, possible minor distortion, security, and difficulty discovering hidden data. This method uses high-frequency 3X3 pixel block patterns to obscure data. The two series of pattern's are identified based on sorted block pattern frequency. To construct a decision tree for embedding, these series patterns, key bits, and information bits work together as parameters. Information is encrypted using a secret key to ensure message security before being hidden. A decision tree decides the block suitability and bit embedding with or without flipping at the sender side. A histogram of 3X3 pixel block patterns gets generated for the received image containing concealed data, and two series are recognized similarly to the embedding procedure at the receiver side. A decision tree assesses whether an image block carries an information bit and decides whether the bit is "0" or "1". This decision tree extracts hidden data bits by analyzing series patterns and key bits. The secret key decodes retrieved concealed bits and reveal the original data. According to research, 50-80 % of hidden bits are transmitted without flipping the pixels, automatically reducing visual distortion. This scheme performs better than comparable methods and is applicable in steganography and watermarking. [ABSTRACT FROM AUTHOR]

The large-scale information interchange that occurs across computer networks in the modern day makes it imperative to protect that information and stop unauthorized individuals from accessing or altering it. Information hiding is one of the critical areas for maintaining information security, preventing unauthorized individuals from accessing and knowing its content. The steganography technique employs various types of media as covers for embedding secret messages. These media can be in the form of images, audio, video, text, and other forms of media. The process of embedding information within text presents several challenges, the most significant of which include the limited available space for concealment and the substantial impact of the hidden data on the text. This research includes a review of the most important techniques and studies used in textbased steganography, presenting their advantages and weaknesses. [ABSTRACT FROM AUTHOR]

Quick response (QR) code-based traceability is considered as a smart solution to know details about the origin of products, from production to transportation and preservation before reaching customers. However, the QR code is easily copied and forged. Thus, we propose a new approach to protect this code from tampering. The approach consists of two main phases like hiding a security feature in the QR code, and estimating the similarity between the QR code affixed on the product and the genuine ones. For the former issue, the secret feature is encoded and decoded by using error correcting code for controlling errors in noisy communication channels. Hiding and extracting the encoded information in the QR code are conducted by utilizing a deep neural network in which the proposed network produces a watermarked QR code image with good quality and high tolerance to noises. The network is capable of robustness against real distortions caused by the process of printing and photograph. For the later issue, we develop neural networks based upon the architecture of Siamese network to measure the similarity of QR codes. The secret feature extracted from the obtained QR code and the result of QR code similarity estimation are combined to determine whether a QR code is genuine or fake. The proposed approach gives a competitive performance, with an average accuracy of 98%, and it has been applied to QR code authentication in practice. [ABSTRACT FROM AUTHOR]

Recently, advancements in multimedia have made a huge impact on watermarking technologies. The digital video watermarking is the process of embedding the data in the video. One of the major concerns in digital video watermarking is maintaining the quality of video besides preserving the privacy of the data. The aim of the research is to develop a reversible medical video watermarking using Sine Cosine Bird Swarm Algorithm-based Deep Convolutional Neural Network (SCBSA-based Deep CNN) for embedding the secret message in video frames. The development methodology is explained as follows. The SCBSA is developed by integrating Sine Cosine Algorithm (SCA) with the Bird Swarm Algorithm (BSA). The key frames are extracted from the input video using Minkowski distance and Wavelet distance. The features, like Neighborhood-based features, Convolutional Neural Network (CNN) features, Local Optimal Oriented Pattern (LOOP), and histogram features are obtained from the key frames. The interesting region is identified using DCNN, which is trained using the developed SCBSA. The secret message is embedded in the video in the embedding phase, whereas the embedded secret message is extracted in the extraction phase. The embedding and extracting process are carried out through two level decompositions using wavelet transform and inverse wavelet transform. The developed SCBSA-based Deep CNN uses the metrics, such as correlation coefficient, Mean Square Error and Peak signal-to-noise ratio (PSNR) for evaluating the performance. The developed SCBSA method is evaluated using the Mean Square Error, Correlation Coefficient and PSNR with Gaussian noise, Impulse noise, Salt and Pepper noise and in the absence of noise. The developed SCBSA method obtained a maximum correlation coefficient of 0.8990, minimum Mean Square Error of 0.0215 and maximum PSNR of 35.19, respectively while comparing with the existing reversible medical video watermarking methods. [ABSTRACT FROM AUTHOR]

The security of information exchange over email and other web-based means is rather low, and there is the risk of interception when it comes to confidential information (e.g., credit card info). Therefore, online users should be ensured of the security and privacy of their web interactions. Despite the remarkable benefits of the Internet in the modern era and its contribution to digital communication, the information security of open networks has become an important issue due to its heavy costs. Several approaches have been used to address this issue, particularly through information hiding and encryption in system security strategies. Cryptography is the process of information encryption, and steganography refers to information hiding. These methods have proven quite effective in maintaining information security. Cryptography involves making changes to confidential information, which prevents their readability by eavesdroppers, which could also be considered a technique of original text to cipher text. On the other hand, steganography entirely hides confidential information from unauthorized users using multiple carrier formats, including audio, video, protocol, and images. Given the availability of digital images, they are often employed as carrier files online. Other approaches to image steganography are also common and have specific limitations and advantages. The present study aimed to review different methods of image cryptography and steganography and compare the studies in this regard so as to determine which the best, specific and accurate methods of information security. [ABSTRACT FROM AUTHOR]

This article proposes a reversible information hiding algorithm based on chaos and histogram translation in ciphertext images to address the shortcomings of traditional algorithms such as separation of encryption and information hiding processes, small embedding capacity, and inflexible operation. This article first uses grayscale images as a carrier for digital images, analyzes and studies existing reversible information hiding algorithms in the ciphertext domain of grayscale images, and improves them to solve the problems of existing reversible information hiding algorithms in the ciphertext domain. Secondly, the sender first encrypts the image and then embeds the information; The receiving end can either decrypt and extract information first, or extract and decrypt information first. Finally, we selected a Lena grayscale image with 513 pixels × 513 pixels for the experiment, dividing the image into 4 blocks (r = 4), and scrambling the pixel positions using DLKL transform for each block, with parameters k = 4, n = 7, q = 59. The simulation results show that the algorithm is easy to implement and can effectively improve the capacity of information embedding.

An increasing volume of malicious software exploits information hiding techniques to cloak additional attack stages or bypass frameworks enforcing security. This trend has intensified with the growing diffusion of mobile ecosystems, and many threat actors now conceal scripts or configuration data within high-resolution icons. Even if machine learning has proven to be effective in detecting various hidden payloads, modern mobile scenarios pose further challenges in terms of scalability and privacy. In fact, applications can be retrieved from multiple stores or directly from the Web or social media. Therefore, this paper introduces an approach based on federated learning to reveal information hidden in high-resolution icons bundled with mobile applications. Specifically, multiple nodes are used to mitigate the impact of different privacy regulations, the lack of comprehensive datasets, or the computational burden arising from distributed stores and unofficial repositories. Results collected through simulations indicate that our approach achieves performances similar to those of centralized blueprints. Moreover, federated learning demonstrated its effectiveness in coping with simple "obfuscation" schemes like Base64 encoding and zip compression used by attackers to avoid detection. [ABSTRACT FROM AUTHOR]

Advances in communication technologies have fueled growth in digital data transfer. Images are one of the most often conveyed types of digital information. Crytographic techniques help create cipher but also lure attackers as it indicates secret communication. To overcome, a method for encrypting a secret image and hiding it in audio data is proposed. The Ikeda map is used to create the encrypted image, which is then hidden in the audio's lifting wavelet transform. Various statistical experiments show that the proposed approach conceals the encrypted image while causing minimal changes to the audio. The proposed algorithm shows robustness towards noise addition or random audio crop attack by retrieving a visually perceivable image after the attack. The suggested approach outperforms the current algorithms in terms of imperceptibility and embedding capacity. [ABSTRACT FROM AUTHOR]

Steganography involves concealing information by embedding data within cover media and it can be categorized into two main domains: spatial and frequency. This paper presents two distinct methods. The first is operating in the spatial domain which utilizes the least significant bits (LSBs) to conceal a secret message. The second method is the functioning in the frequency domain which hides the secret message within the LSBs of the middle-frequency band of the discrete cosine transform (DCT) coefficients. These methods enhance obfuscation by utilizing two layers of randomness: random pixel embedding and random bit embedding within each pixel. Unlike other available methods that embed data in sequential order with a fixed amount. These methods embed the data in a random location with a random amount, further enhancing the level of obfuscation. A pseudo-random binary key that is generated through a nonlinear combination of eight Linear Feedback Shift Registers (LFSRs) controls this randomness. The experimentation involves various 512x512 cover images. The first method achieves an average PSNR of 43.5292 with a payload capacity of up to 16% of the cover image. In contrast, the second method yields an average PSNR of 38.4092 with a payload capacity of up to 8%. The performance analysis demonstrates that the LSB-based method can conceal more data with less visibility, however, it is vulnerable to simple image manipulation. On the other hand, the DCT-based method offers lower capacity with increased visibility, but it is more robust. [ABSTRACT FROM AUTHOR]

A two-echelon supply chain comprising a single retailer and a single manufacturer is investigated. The retailer may adopt different demand information sharing strategies. Likewise, the manufacturer may decide to encroach, or not encroach, on the retailer's space. The impact of such different decisions on the expected profits and strategies of both sides is discussed. The results reveal that: (1) Sharing or hiding demand information can lead to manufacturer encroachment; (2) Under each retailer's demand information sharing strategy, there are encroachment areas where Pareto improvement can be achieved; (3) Information sharing may not always benefit the manufacturer, and information hiding may not always be detrimental to the manufacturer. The effects of demand correction values and promotion fees on the strategies of both sides of the supply chain are further discussed in conjunction with numerical simulations. [ABSTRACT FROM AUTHOR]

Generation-based linguistic steganography is a popular research area of information hiding. The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to. However, in the course of our experiment, we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text, which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases, and that the topic of generated texts is uncontrollable, so there is still room for improvement in concealment. In this paper, we propose a topic-controlled steganography method which is guided by graph-to-text generation. The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs, and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation. Different from traditional linguistic steganography methods, we encode the secret information during graph path coding rather than using conditional probability. We test our method in different aspects and compare it with other text generative steganographic methods. The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text. [ABSTRACT FROM AUTHOR]

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The paper presents the analysis of the Commercial Off-The-Shelf (COTS) software regarding the ability to be used in audio steganography techniques. Such methods are a relatively new tool for hiding and transmitting crucial information, also being used by hackers. In the following work, the publicly available software dedicated to audio steganography is examined. The aim was to provide the general operating model of the information processing in the steganographic effort. The embedding method was analyzed for each application, providing interesting insights and allowing classifying the methods. The results prove that it is possible to detect the hidden message within the specific audio file and identify the technique that was used to create it. This may be exploited further during the hacking attack detection and prevention.

Aiming at the problem of low amount of information carried by the existing block timestamp interval hiding method, a multi-address time-based blockchain covert communication method was proposed.Firstly, the ciphertext was split and transmitted by different addresses.The content of the ciphertext fragment was represented by the block timestamp interval of the address.Then the interval of the blocks was read and counted by the receiver where these addresses were located.Finally, the ciphertext was restored by combination.In addition, in view of the lack of concealment measures in the time-based blockchain covert communication system, a method of adjusting the time interval of transaction initiation was proposed to reduce the probability of address specificity caused by covert communication behavior.The experimental results verify that the transmission rate of the proposed method is about n times higher than that of the time-based blockchain covert communication method when n addresses are involved.

Most current JPEG steganalytic methods can only extract features from a series of linear residuals.Non-linear filters are not considered in these JPEG steganalytic methods, resulting in single types of residuals.Hence, a JPEG steganalytic method using non-linear residuals was proposed.Firstly, non-linear residuals were generated without a high computational cost by using element-wise minimum and maximum operations across a couple of linear residuals which had been obtained in the current JPEG steganalytic method.Secondly, according to the JPEG phase, the non-linear residual was divided into sub-residuals in which the histogram features were extracted.Thirdly, considering the minimum and maximum operators, the symmetrization method was accordingly designed.Finally, all the symmetrized histogram features were concatenated to form the final feature set.Experimental results indicate that the performance for JPEG steganalysis can be improved effectively by using both the linear and the non-linear residuals.

The past decades witness a tremendous exchange in data and information in almost all domains. This leads to the need for applying data security to ensure information safety during communication. One of the main used technique is the steganography. Steganography is a technique that involves hiding information within objects, such as images, audio, video, or 3D objects, without leaving any noticeable alterations. We propose a 3D steganographic technique that increases security using Gray-code sequence and a Least Significant Bit technique. We construct the 64-binary representation for the 3D cover-object. A Gray-code sequence defined the 3D object vertices that will be utilized for concealing the information. The binary representation of the information is to be concealed in the least significant bits of either the x- or the y-components of the defined vertices. The least significant bits, are the last two bits in the binary representation of the vertex components. Exploitation the binary representation, gives us the capability of increasing the data security, and the data capacity. The proposed steganographic technique has been evaluated through multiple evaluation metrics to assess its performance; including Mean Square Error Ratio, Peak Signal-to-Noise Ratio, Histogram, and Normalized Correlation Experimental results, indicate that the security level of the proposed technique is superior comparing to several existed techniques. Moreover, when testing against some common attacks such as the noise, the median, the Gaussian and the Laplacian filters; the results show the efficiency and the robustness of the proposed technique.

The technique of information hiding is very important in achieving security of important and sensitive data, especially those that are transmitted through various digital communication channels because it has robust characteristics that distinguish it from encryption techniques, the most important of which is that it is not perceived by protrusive and hackers, as it is based on the principle of hiding those data inside other digital media as a carrier cover. On the other hand, with the development of hiding techniques, techniques developed to try extracting its hiding to hacking its contents, for this reason and to increase the efficiency of these methods, the encryption and hiding techniques was combined together.The proposed method depends on distributing secret data on several digital audio files of type WAV in random way depends on circular secret key values that is generated in random order that be agreed upon between the sender and the receiver. This technique has achieved high durability, and in the event of suspicion of the existence of secret content within any WAV file, the multiplicity of carrier files and their different length, as well as random distribution of data in them, all these characteristic eliminates the suspicion of any confidential content, as well as complicates the file retrieved process if the suspicion be occurs.

Information hiding is an important technique for security-related applications, and it can be used wildly in many scenarios. Secret data embedding methods are proposed in spatial, frequency, and other domains by researchers in recent years. After investigating the existing information hiding schemes, we find that there is still room to improve the data embedding performance. Inspired by some works of literature, we propose a new scheme based on the modulus function with Minimum Pixel Modification (MPM22) for hiding secret data into carriers. The main idea of the scheme is to embed confidential bits into cover-image pixels while minimizing modification to original pixels. The correctness and high performance of the scheme are proved in mathematics and comprehensive experiments. Experimental result shows MPM22 has the largest embedding capacity (3 36.1 dB@k=3, PSNR>30.5 dB @k=4)。 The experimental result also confirms that our proposed scheme has higher performance than other schemes.

Despite the rapidly growing studies on Arabic text steganography (ATS) noted recently; systematic, in-depth, and critical reviews are in scarcity due to high overlap or low segregation level among the existing review articles linked to this research area. As such, the objective of this paper is to present an extensive systematic literature review (SLR) on the techniques and algorithms used to analyse ATS. Data were retrieved from three primary databases, namely Science direct Journal, IEEE Explore Digital Library, and Scopus Journal. As a result, 214 publications were identified since the past 5 years regarding methods of analysing ATS. A comprehensive SLR was executed to detect a range of unique characteristics from the algorithms, which led to the discovery of a new structure of ATS categories. Essentially, a hybrid method for ATS was identified with other sub-disciplines, especially cryptography, which leads to a new branch in enhancing security for ATS. Other relevant findings included key performance and evaluation criteria used to measure the performance of the algorithms (i.e., capacity, invisibility, robustness, & security). 87 % of the reviewed articles are the capacity measurement performance. Therefore, it disclosed a huge potential for the other two criteria (i.e. invisibility, robustness and security) to set a benchmark for future research endeavour.