Design secure multi-level communication system based on duffing chaotic map and steganography

Cryptography and steganography are among the most important sciences that have been properly used to keep confidential data from potential spies and hackers. They can be used separately or together. Encryption involves the basic principle of instantaneous conversion of valuable information into a specific form that unauthorized persons will not understand to decrypt it. While steganography is the science of embedding confidential data inside a cover, in a way that cannot be recognized or seen by the human eye. This paper presents a high-resolution chaotic approach applied to images that hide information. A more secure and reliable system is designed to properly include confidential data transmitted through transmission channels. This is done by working the use of encryption and steganography together. This work proposed a new method that achieves a very high level of hidden information based on non-uniform systems by generating a random index vector (RIV) for hidden data within least significant bit (LSB) image pixels. This method prevents the reduction of image quality. The simulation results also show that the peak signal to noise ratio (PSNR) is up to 74.87 dB and the mean square error (MSE) values is up to 0.0828, which sufficiently indicates the effectiveness of the proposed algorithm.

Video steganography using 3D distance calculator based on YCbCr color components

Steganography techniques have taken a major role in the development in the field of transferring multimedia contents and communications. Therefore, field of steganography become interested as the need for security increased significantly. Steganography is a technique to hide information within cover media so that this media does not change significantly. Steganography process in a video is to hide the information from the intruder and prevent him access to that hidden information. This paper presents the algorithm of steganography in the video frames. The proposed algorithm selected the best frames to hide the message in video using 3D distance equation to increasing difficulty onto the intruder to detect and guess the location of the message in the video frames. As well as selected the best frames in this algorithm increased the difficulty and give us the best stego-video quality using structural similarity (SSIM). Also, the hash function was used to generate random positions to hide the message in the lines of video frames. The proposed algorithm evaluated with mean squared error (MSE), peak signalto-noise ratio (PSNR) and SSIM measurement. The results were acceptable and shows that is the difficulty of distinguishing the hidden message in stego-video with the human eye.

Economic and environmental assessment of an unreliable supply chain management

The retailers within a supply chain management are the most important player as it has direct contact with the customers. Customers are the source of the money and information for the entire supply chain management. The equilibrium condition of the forward and backward supply chain is tight until it is reliable. But sometimes the retailers hide information from the manufacturer and this unreliability starts to propagate to the entire supply chain management. Blockchain technology is one of the secure decentralized systems to prevent unreliability. This study eliminates the unreliability of the system. A mathematical model is derived where the vendor-managed inventory policy is used by the single manufacturer to deal with multiple unreliable retailers. The entire process of manufacturing emits carbon. The carbon emission is controlled by the cap and trade policy and by paying the carbon tax. The results are found by the classical optimization technique and the numerical studies open up a way to the blockchain to deal with unreliable retailers. The decentralized system is a probable choice to prevent unreliability and thus the blockchain.

Two-Layer Reversible Data Hiding for VQ-Compressed Images Based on De-Clustering and Indicator-Free Search-Order Coding

During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in compressed images is a hot issue recently. In this paper, we apply the de-clustering concept and the indicator-free search-order coding (IFSOC) technique to hide information into vector quantization (VQ) compressed images. Experimental results show that the proposed two-layer reversible data hiding scheme for IFSOC-encoded VQ index table can hide a large amount of secret data among state-of-the-art methods with a relatively lower bit rate and high security.

Secure Data Transfer over Internet Using Image Steganography: Review

Whether it's for work or personal well-being, keeping secrets or private information has become part of our everyday existence. Therefore, several researchers acquire an entire focus on secure transmitting secret information. Confidential information is collectively referred to as Steganography for inconspicuous digital media such as video, audio, and images. In disguising information, Steganography plays a significant role. Traditional Steganography faces a further concern of discovery as steganalysis develops. The safety of present steganographic technologies thus has to be improved. In this research, some of the techniques that have been used to hide information inside images have been reviewed. According to the hiding domain, these techniques can be divided into two main parts: The spatial Domain and Transform Domain. In this paper, three methods for each Domain have been chosen to be studied and evaluated. These are; Least Significant Bit (LSB), Pixel Value Difference (PVD), Exploiting Modification Direction (EMD), contourlet transform, Discrete Wavelet Transformation (DWT), and, Discrete Cosine Transformation (DCT). Finally, the best results that have been obtained in terms of higher PSNR, Capacity, and more robustness and security are discussed.

Steganographic methods in vector graphics

Various steganographic techniques are used to hide information. Usually, information is hidden in images, audio and video files, text documents, and the like. The article deals with vector images consisting of various mathematical objects (points, lines, curves of the first and second order, Bezier curves, nodes, tangents, base points, etc.). Information hiding techniques alter these mathematical objects, for example, by encoding the coordinates of the base points. The most successful for carrying out steganographic transformations is the SVG vector graphics format, which, due to its structure, makes it easy to manipulate the objects of which it consists. Its broad support across platforms also allows for increased secrecy when transferring sensitive data by sending seemingly ordinary media files. The article discusses two methods (bitwise and the method of patterns) of hiding information in vector images, studied their features, advantages and disadvantages. Various affine transformations that can be used to disrupt the operation of the steganosystem were also investigated. The most common types of affine transformations are the operations of transfer, rotation, shift and scaling with possible variations (offsets along the abscissa and ordinate axes, proportional and non-proportional scaling, with compression and expansion). Most of the methods for embedding information into vector images provide a one-time resistance to affine transformations, while the repeated imposition of operations for changing the position of objects may destroy the message altogether. The methods investigated in the work (bitwise and the method of patterns) implement a higher level of resistance to various kinds of transformations when they are repeated many times, and the conducted experiments clearly demonstrate this. The results obtained show that vector images can indeed be used to hide information, but the resistance against certain affine attacks is not always high.

Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview

Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification.

METHOD FOR STEGANOGRAPHIC HIDE OF INFORMATION BASED ON CONTINUOUS WAVELET TRANSFORM

This article discusses continuous wavelet transform as a method of steganographic embedding of confidential information into an image. The main purpose of steganography is to hide information so that the possibility of data detection is minimized. This is done by hiding the message inside the container so that outsiders are not aware of the secret’s existence. Thus, the main principle of steganography is the principle of invisibility, which is also the basis of security when using these systems to transfer information. Steganography methods are divided into two large groups: spatial and frequency. The former visually degrade the image quality by directly changing the components (pixels). The latter interact with frequency characteristics, which has the best effect on the quality of the converted image. At this point in time, one of the most common frequency methods (discrete-cosine transform) is increasingly being replaced by a wavelet transform. This method of embedding confidential information is visually less noticeable to human vision, relative to those existing at a given time.The paper presents brief theoretical information on the wavelet transform, gives the characteristics of the Haar transform, presents images demonstrating the principle of the wavelet transform. The developed algorithm for steganography based on the wavelet transform is shown. The algorithm was implemented in the Matlab environment, as well as the analysis of the results obtained using the example of a test image. Conclusions, advantages of this method, as well as recommendations for further research in this area are given.

Audio Forensics on Smartphone with Digital Forensics Research Workshop (DFRWS) Method

Audio is one of the digital items that can reveal a happened case. However, audio evidence can also be manipulated and changed to hide information. Forensics audio is a technique to identify the sound’s owner from the audio using pitch, formant, and spectrogram parameters. The conducted research examines the similarity of the original sound with the manipulated voice to determine the owner of the sound. It analyzes the level of similarity or identical sound using spectrogram analysis with the Digital Forensics Research Workshop (DFRWS) Method. The research objects are original and manipulated files. Both files are in mp3 format, which is encoded to WAV format. Then, the live forensics method is used by picking up the data on a smartphone. Several applications are also used. The results show that the research successfully gets digital evidence on a smartphone with the Oxygen Forensic application. It extracts digital evidence in the form of two audio files and two video files. Then, by the hashing process, the four obtained files are proven to be authentic. Around 90% of the data are identical to the original voice recording. Only 10% of the data are not identical.