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The art of identifying steganographic traces from digital media images is termed steganalysis. The secret message embedded into the digital media files may be text, audio, video, or in the form of an image. The detection of secret hidden information from the images is carried out using Image steganalysis. The detection and extraction of existing hidden secret messages from the original image are difficult. Hence, an optimization-based deep learning model for detecting hidden information is designed here. In this research, the designed CAViaR Student Psychology-based Optimization-Deep Maxout Network (CSPBO-DMN) technique is used for recovery of the original image through steganography and steganalysis. The bit map image is generated from the cover image and the hidden secret message is XOR-ed with a key. Discrete wavelet transform (DWT)-based embedding, Least-significant bit (LSB)-based embedding and Discrete Cosine Transform (DCT)-based embedding techniques are the XOR-ed and bit map image output. Later, using the DMN classifier, the secret message is detected from the bit map image, which is trained using the CSPBO technique. The experimental outcomes proved that the CSPBO-DMN approach attained higher performance with a Peak-Signal-to-Noise Ratio (PSNR), Bit Error Ratio (BER), computational complexity and memory usage of 35.275 dB, 5.658, 1.225 and 0.017, respectively.

Steganography is a data hiding method mainly used in the security purposes. While hiding more data in the embedding process the data may be lost and also cause some security problems. To avoid this problem a Steganography Embedding method is used. In this manuscript, Steganography Embedding method based on Cohen–Daubechies–Feauveau Discrete Wavelet Transform (CDF-DWT) technique to data hiding application using Elgamal algorithm is proposed. In this the cover image is taken for hiding the secret data. Then the cover image edges are detected and filtered with Speeded-Up Robust Features (SURF) method. Then the input secret data is encrypted with Elgamal algorithm. Then the secret data is hided under cover image for obtaining the stego image by process of Embedding using CDF DWT technique. In this data in the stego images are unreadable. To get readable secured data is extracted from the stego image and the data’s are decrypted to get secured secret data. The objective of this method is to safe guard the secret using Steganography method and to increase embedding efficiency, Embedding capacity and carrier capacity and to reduce the execution time. The MATLAB simulation results of the proposed CDF DWT technique with Elgamal algorithm portrays better outcomes such as Peak to Signal Noise Ratio (PSNR), Mean Square Error (MSE) (lower), Bit Error Rate (BER) was Lower, Execution time provides is lower, Carrier Capacity and Embedding Capacity are much higher and the values are compared with the existing method such as Elliptic Galois in cryptography and in the Steganography method with Adaptive Firefly Algorithm (EGC-AFA), Reversible Data hiding within Encrypted images Via Adaptive Embedding Strategy with block selection (RDHEI-AES), Double Linear Regression Prediction based Reversible Data Hiding in Encrypted Image (DLRP-RDHEI) respectively.

The typical model of steganography has led the prisoners' problem, in which two persons attempt to communicate covertly without alerting the warden. The general way to achieve this task is to embed the message in an innocuous-looking medium. In this paper, an object-based geometric embedding technique is proposed for solving the prisoners' problem. The main idea is to embed secret data through distorting a given object and the distorted object still looks natural. In the embedding process, the secret message is first converted into coefficients of an affine transformation. Then, the coordinates of each pixel of a selected object in the cover-image are recomputed by this affine transformation. Since these coefficients are restricted in a specific range, the transformed object looks natural. In the extracting process, a coarse-to-fine iterative search is proposed to accelerate the object location and the message extraction. Experimental results show that all transformed objects can be located precisely and the whole hidden message can be extracted correctly even if the stego-image is stored in various compression formats and rates. Furthermore, the embedded message is robust enough when the stego-image format is converted from GIF to JPEG, and vice versa.

The typical model of steganography has led the prisoners' problem, in which two persons attempt to communicate covertly without alerting the warden, that is, only the receiver knows the existence of the message sent by the sender. One available way to achieve this task is to embed the message in an innocuous-looking medium. In this paper, we propose a variation of the Quantization Index Modulation (QIM) for solving the prisoners' problem. We also propose a theorem to show that the error of mean intensity value of an image block caused by JPEG compression is bounded. The proposed method embeds the messages to be conveyed by modifying the mean intensity value, and the resulting stego-image can be stored in the JPEG format with a low quality setting. Besides, a specific pattern caused by using the QIM embedding method is also identified, and this pattern will be removed using the proposed embedding method. Experimental results and the proposed theorem show that the hidden message is error-free against the JPEG distortion under the quality setting as low as 25. Furthermore, the existence of the hidden message is not only visually imperceptible but also statistically undetectable.

In this paper, a novel gray-level image-hiding scheme is proposed. The goal of this scheme is to hide multiple important gray-level images into another meaningful gray-level image. The secret images to be protected are first compressed using the vector quantization scheme. Then, the DES cryptosystem is conducted on the VQ indices and related parameters to generate the encrypted message. Finally, the encrypted message is embedded into the rightmost two bits of each pixel in the cover image.

According to the experimental results, average image qualities of 44.320 dB and 30.885 dB are achieved for the embedded images and the retrieved secret images, respectively. In other words, multiple secret images can be effectively hidden into one host image of the same size. In addition, the proposed scheme strengthens the protection of the secret images by conducting the DES cryptosystem on the related parameters and the VQ indices of the compressed secret images. Therefore, the proposed scheme provides a secure approach to embed multiple important images into another meaningful image of the same size.

This paper proposes a method for hiding an important image in a cover image whose size is limited. In this method, in order to save space, a modified search-order coding (MSOC) technique first transforms the important image, then, a randomization procedure permutes the transformed image to further increase the security. Finally, a modulus function embeds the permuted code in a cover image; notably, in the modules function, the modulus base used for a pixel is determined according to the variance of its neighboring pixels. Experimental results show that the images are of high quality. Comparisons with reported methods are provided.

In this paper, we propose a novel steganographic method, which utilizes the sparsity and integrity of the image compressed sensing to reduce the risk of being detected by steganalysis. In the proposed algorithm, the message hiding process is integrated into the image sparse decomposition process without affecting the image perceptibility. First, the cover image is decomposed by the orthogonal matching pursuit algorithm of image sparse decomposition, and the shuffled frog leaping algorithm (SFLA) is used to select the optimal atom in each decomposition iteration. Then, different quantization bits are adopted to quantify the sparse decomposition coefficients. Finally, via LSB$\pm k$ steganographic strategy, the secret message is embedded in the least significant bits of the quantized coefficients. Experimental results show that the embedded data are invisible perceptually. Simultaneously, experiments show that the new steganography has good expandability in embedding capacity, owing to less sensitivity to the embedding bits. The security of the proposed method is also evaluated comparatively, by using four steganalyzers with rich feature, which indicates superior performance of the proposed method comparing with other steganographies conducted in sparse decomposition domain and the LSB$\pm k$ methods used in spatial domain and DCT domain.

In Digital Image Steganography, Pixel-Value Differencing (PVD) methods use the difference between neighboring pixel values to determine the amount of data bits to be inserted. The main advantage of these methods is the size of input data that an image can hold. However, the fall-off boundary problem and the fall in error problem are persistent in many PVD steganographic methods. This results in an incorrect output image. To fix these issues, usually the pixel values are either somehow adjusted or simply not considered to carry part of the input data. In this paper, we enhance the Tri-way Pixel-Value Differencing method by finding an optimal pixel value for each pixel pair such that it carries the maximum input data possible without ignoring any pair and without yielding incorrect pixel values.

This paper proposes an information hiding algorithm using matrix embedding with Hamming codes and histogram preservation in order to keep the histogram of the image unchanged before and after hiding information in digital media. First, the algorithm uses matrix embedding with Hamming codes to determine the rewriting bits of the original image, rewrite and flip them, and successfully embed the secret information. Then, according to the idea of a break-even point, a balanced pixel frequency adaptive algorithm is proposed and each embedded bit of secret information is detected and compensated by the adjacent bit of histogram data, so that the histogram change of the image before and after information hiding is minimized. At present, most of the histogram distortion values after steganography are generally over 1000 or even higher. As a contrast, the method proposed in this paper can keep the histogram distortion values to be less than 1000. The feasibility and effectiveness of the algorithm are verified by relative entropy analysis as well. The experimental results also show that the algorithm performs well in steganographic analyses of images.

In this paper, a steganography algorithm has been proposed which is based on quantization table modification and image scrambling in the DCT domain. First, the algorithm homogenizes the energy by scrambling the cover image to improve the number of DCT coefficients suitable for information embedding. Second, the embedding capacity of the DCT block is determined by the value of the quantization table in the algorithm, different quantization tables get different embedding effects. In addition, this paper proposes an optimized modified quantization table. Extensive experiments show that the proposed algorithm achieves a great potential for confidential data and indiscernible image quality.

Data hiding in the LSB of audio signals is an appealing steganographic method. This is due to the large volume of real-time production and transmission of audio data which makes it difficult to store and analyze these signals. Hence, steganalysis of audio signals requires online operations. Most of the existing steganalysis methods work on stored media files. In this paper, we present a steganalysis technique that can detect the existence of embedded data in the least significant bits of natural audio samples. The algorithm is designed to be simple, accurate, and to be hardware implementable. Hence, hardware implementation is presented for the proposed algorithm. The proposed hardware analyzes the histogram of an incoming stream of audio signals by using a sliding window strategy without needing the storage of the signals. The algorithm is mathematically modeled to show its capability to accurately predict the amount of embedding in an incoming stream of audio signals. Audio files with different amounts of embedded data were used to test the algorithm and its hardware implementation. The experimental results prove the functionality and high accuracy of the proposed method.

Steganography has become one of the most significant techniques to conceal secret data in media files. This paper proposes a novel automated methodology of achieving two levels of security for videos, which comprise encryption and steganography techniques. The methodology enhances the security level of secret data without affecting the accuracy and capacity of the videos. In the first level, the secret data is encrypted based on Advanced Encryption Standard (AES) algorithm using Java language, which renders the data unreadable. In the second level, the encrypted data is concealed in the video frames (images) using FPGA hardware implementation that renders the data invisible. The steganographic technique used in this work is the least significant bit (LSB) method; a 1–1–0 LSB scheme is used to maintain significantly high frame imperceptibility. The video frames used as cover files are selected randomly by the randomization scheme developed in this work. The randomization method scatters the data throughout the video frames rendering the retrieval of the data in its original order, without a proper key, a challenging task. The experimental results of concealment of secret data in video frames are presented in this paper and compared with those of similar approaches. The performance in terms of area, power dissipation, and peak signal-to-noise ratio (PSNR) of the proposed method outperformed traditional approaches. Furthermore, it is demonstrated that the proposed method is capable of automatically embedding and extracting the secret data at two levels of security on video frames, with a 57.1dB average PSNR.

A highly secure communication method is essential for end users for the exchange of information which is not interpreted by an intruder. Cryptography plays a crucial role in the current and upcoming digital worlds, for secure data transmission in wired and wireless networks. Asymmetric and symmetric cryptographic algorithms encrypt data against vulnerable attacks and transfer to authenticated users. Steganography is a method for providing secure information with the help of a carrier file (text, video, audio, image, etc.). This paper proposes Deoxyribonucleic Acid (DNA)-based asymmetric algorithm which is used to encrypt the patient’s secret information and its performance is compared with ElGamal, RSA and Diffie–Hellman (DH) cryptographic algorithms. The proposed asymmetric algorithm is applied to image steganography which is used for encrypting and concealing the patient’s secret information in a cover image. The proposed method consumes less hardware resources with improved latency. Dynamic Partial Reconfiguration (DPR) allows to transform a selective area rather than complete shutdown of the entire system during bitstream configuration. Cryptosystem with DPR is designed, synthesized in Xilinx Vivado and simulated in Vivado simulator. The design is targeted at Basys3, Nexys4 DDR and Zync-7000 all-programmable SOC (AP SoC) architectures and programmed with secure partial bit files to avoid vulnerable attacks in the channel.

Chaotic maps have been widely used in image encryption due to their complexity, pseudorandomness and high sensitivity to initial values. In this paper, an image encryption algorithm based on a 4D chaotic map and steganography is proposed. The algorithm consists of two rounds of encryption and one operation of embedding hash. In the first round of encryption, the hash value of plaintext image is used to control the generation of chaotic sequences, which makes the encryption algorithm highly relevant to the content of the image. Then, the hash value is embedded into the intermediate image according to the idea of steganography. In the second round of encryption, the image is encrypted under the control of another set of chaotic sequences to hide the hash value and further enhance the security of the algorithm. Different from other algorithms, our algorithm does not need to additionally transmit the hash value to the decryptor through a special channel. It has good availability and adaptability. Experimental results and security analysis demonstrate that the algorithm has high security performance and can resist various attacks.

In this paper, we present a novel technique for security of two-dimensional data with the help of cryptography and steganography. The presented approach provides multilayered security of two-dimensional data. First layer security was developed by cryptography and second layer by steganography. The advantage of steganography is that the intended secret message does not attract attention to itself as an object of scrutiny. This paper proposes a novel approach for encryption and decryption of information in the form of Word Data (.doc file), PDF document (.pdf file), Text document, Gray-scale images, and RGB images, etc. by using Vigenere Cipher (VC) associated with Discrete Fourier Transform (DFT) and then hiding the data behind the RGB image (i.e. steganography). Earlier developed techniques provide security of either PDF data, doc data, text data or image data, but not for all types of two-dimensional data and existing techniques used either cryptography or steganography for security. But proposed approach is suitable for all types of data and designed for security of information by cryptography and steganography. The experimental results for Word Data, PDF document, Text document, Gray-scale images and RGB images support the robustness and appropriateness for secure transmission of these data. The security analysis shows that the presented technique is immune from cryptanalytic. This technique further provides security while decryption as a check on behind which RGB color the information is hidden.

In this paper we introduce and develop a framework for visual data-hiding technologies that aim at resolving emerging problems of modern multimedia networking. First, we introduce the main open issues of public network security, quality of services control and secure communications. Secondly, we formulate digital data-hiding into visual content as communications with side information and advocate an appropriate information-theoretic framework for the analysis of different data-hiding methods in various applications. In particular, Gel'fand-Pinsker channel coding with side information at the encoder and Wyner-Ziv source coding with side information at the decoder are used for this purpose. Finally, we demonstrate the possible extensions of this theory for watermark-assisted multimedia processing and indicate its perspectives for distributed communications.

This paper presents methods for performing steganography and steganalysis using a statistical model of the cover medium. The methodology is general, and can be applied to virtually any type of media. It provides answers for some fundamental questions that have not been fully addressed by previous steganographic methods, such as how large a message can be hidden without risking detection by certain statistical methods, and how to achieve this maximum capacity. Current steganographic methods have been shown to be insecure against simple statistical attacks. Using the model-based methodology, an example steganography method is proposed for JPEG images that achieves a higher embedding efficiency and message capacity than previous methods while remaining secure against first order statistical attacks. A method is also described for defending against "blockiness" steganalysis attacks. Finally, a model-based steganalysis method is presented for estimating the length of messages hidden with Jsteg in JPEG images.

In print-type steganography and watermarking, visible calibration patterns are arranged around content in which invisible data are embedded, to provide plural feature points for normalization of a scanned image. However, it is clear that conventional visible calibration patterns interfere with the page layout and artwork of original contents. Additionally, visible calibration patterns are not suitable for security services. In this paper, we propose an arrangement of and a detection method for an invisible calibration pattern based on human visual perception. We embed the proposed calibration pattern in an original image by adding a high-frequency component to blue intensity in limited regions. The proposed method protects the page layout and artwork because it is difficult for observers to detect the calibration pattern embedded into an image with a normal background.

With our lives trundling toward a fully-digital ecosystem in break-neck speed, today’s encryption and cryptography are facing the challenge of ensuring security and future-readiness of our transactions. When such transactions involve multiple hands, transmission of such data in discrete and recoverable parts (secret shares) guarantees confidentiality. This paper’s objective is to present a foolproof way of multiple secret sharing, eliminating issues such as half-toning and degradation of visual quality of the recovered images. This $k$ out of $n$ steganography and authenticated image sharing (SAIS) scheme for multiple color images generates $n$ relevant shares with the ability to reconstruct the secret images using $k$ shares and facility to find out any move for appropriation of share cover images. The key aspects of this proposed scheme is to use simple Boolean and arithmetic operations with reduction of computational complexity from $O(n{log}^{2}n)$ to $O(n)$ and to share multiple images without any pixel expansion.

Conventional techniques for security of data, designed by using only one of the security mechanisms, cryptography or steganography, are suitable for limited applications only. In this paper, we propose a crypto-stego system that would be appropriate for secure transmission of different forms of data. In the proposed crypto-stego system, we present a mechanism to provide secure transmission of data by multiple safety measures, firstly by applying encryption using Affine Transform and Discrete Cosine Transform (DCT) and then merging this encrypted data with an image, randomly chosen from a set of available images, and sending the image so obtained to the receiver at the other end through the network. The data to be sent over a communication channel may be a gray-scale or colored image, or a text document (doc, .txt, or .pdf file). As it is encrypted and sent hidden in an image, it avoids any attention to itself by the observers in the network. At the receiver’s side, reverse transformations are applied to obtain the original information. The experimental results, security analysis and statistical analysis for gray-scale images, RGB images, text documents (.doc, .txt, .pdf files), show robustness and appropriateness of the proposed crypto-stego system for secure transmission of the data through unsecured network. The security analysis and key space analysis demonstrate that the proposed technique is immune from cryptanalysis.