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![3D Steganography using chaotic map and the LSB technique [59].](publication/354889822/figure/fig4/AS:11431281093099286@1667098094791/3D-Steganography-using-chaotic-map-and-the-LSB-technique-59.png)
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![Figure 4. Multilayer data hiding using LSB [57].](publication/354889822/figure/fig3/AS:11431281093071653@1667098094743/Multilayer-data-hiding-using-LSB-57_Q320.jpg)
![Figure 6. 3D Steganography using chaotic map and the LSB technique [59].](publication/354889822/figure/fig4/AS:11431281093099286@1667098094791/3D-Steganography-using-chaotic-map-and-the-LSB-technique-59_Q320.jpg)
![Figure 8. 3D image steganography with encryption [61].](publication/354889822/figure/fig5/AS:11431281093080104@1667098094852/3D-image-steganography-with-encryption-61_Q320.jpg)
Steganography has become a preferred technique these days to successfully hide secret messages. Various research has been done in the past to justify and analyze suitable types of cover file, such as images, audio, videos, etc. Advancement in the image-processing domain has opened various possibilities of using three-dimensional (3D) images as cove...
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Recent advancements in steganography analysis based on deep neural networks have led to the development of steganography schemes that incorporate deep network technology like adversarial example, GAN, and reinforce learning. However, most deep network-based steganography schemes are unable to ensure error-free extraction of secret information becau...
Steganography is the approach for hiding any secret message in a variety of multimedia carriers like images, audio or video files. Whenever we are hiding a data, it is very important to make it invisible, so that it could be protected. A number of steganographic algorithms have been proposed based on this property of a steganographic system. This p...
![Figure 2. Universal deep hiding (UDH) framework proposed in [10].](publication/357831375/figure/fig2/AS:1114733931446293@1642784688949/Universal-deep-hiding-UDH-framework-proposed-in-10_Q320.jpg)
Data hiding is the technique of embedding data into video or audio media. With the development of deep neural networks (DNN), the quality of images generated by novel data hiding methods based on DNN is getting better. However, there is still room for the similarity between the original images and the images generated by the DNN models which were t...
Recently, deep learning based audio steganalysis methods have demonstrated superior performance in detecting the conventional audio steganography, which poses great chanllegnes to the conveiontional audio steganography. In this work, observed that the neural network can easily be deceived by specially perturbed inputs, i.e., adversarial examples, w...
Traditional audio steganography by cover modification causes changes to the cover features during the embedding of a secret, which is easy to detect with emerging neural-network steganalysis tools. To address the problem, this paper proposes a coverless audio-steganography model to conceal a secret audio. In this method, the stego-audio is directly...
Citations
... S. Dhawan et al. [45]: They propose a steganography method that combines a Salp Swarm-Based Optimization Algorithm (SSOA) with a Deep Enhanced Stacked Auto Encoder (DESAE). This hybrid algorithm aims to enhance the quality of the steganographic process, likely ensuring better hiding of information within the data. ...
... The carrier file is taken in the form of images in both the mentioned tools. At the receiver side, secret information is retrieved for its use by applying some extraction algorithm [5][6][7]. The complete process of embedding and retrieval of secret data is shown with the help of screenshots of the tool used. ...
In the research work, the examination of concealing algorithms, extraction algorithms, carrier multimedia file, and other security parameters has been done for two steganography tools. From the experimental results, we strongly recommend that many of the open-source tools are not safe for embedding personal information as it can be detected with the help of the steganalysis tools that exist in the market. In this research work, stego file is analyzed based on distortion induced concerning the position of bit used for embedding, distortion pattern using histogram, spectrum analysis, similarity index, and entropy. Quantitative values of mentioned parameters are calculated in Python and emphasize the unfortunate present state of the art of realistic steganography tools. At present, there is a lack of publically available secure steganography tools.
... The authors of [21] presented the use of 3D steganography has been thoroughly investigated. The authors of [9] suggested two security approaches using corner detection as an image processing tool, steganography in 3D cover objects, and data encryption. ...
Lately, people are relying on the internet, so it is crucial for them to have a technique for controlling the usage of digital content, such as software, music, movies, and e-books. It restricts access to content by encrypting it and using technological tools like encryption keys and digital signatures. Steganography is used to hide messages and keep them from being intercepted. Steganography and cryptography are combined to provide a higher level of security by using LSB embedding using palindrome sequence. The proposed scheme used image dimensions of 512*512 pixels. The proposed solution performs in a comparable manner in its counterparts in the literature. Presented on Lena, Mandrill, Peppers and House 2 to be compared to other schemes.
... Multimedia files in 3D are increasingly important in many standard applications, including education, entertainment, games, business, video conferencing, marketing, advertising, and more. Consequently, numerous 3D-data hiding techniques have been developed by researchers and academics [12]. The primary benefit of utilizing a 3D object over a 2D image in steganographic techniques is its capability to hide more bits of the message due to the larger number of vertices in a 3D object. ...
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, and 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 (LSB) technique. We construct the 64-binary representation for the 3D cover-object. A Gray code sequence is utilized to define the vertices that will be utilized for embedding the secret message. The binary representation of the secret message is to be hidden in the least significant bits of either the x- or the y- coordinates of the defined vertices. The least significant bits, are the last two bits in the binary representation of the vertex coordinates. 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 (MSE), Peak Signal-to-Noise Ratio (PSNR), and Normalized Correlation (NC). Experimental results, show 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.
