National Institute of Standards and Technology における超伝導研究及び生活

Due to the significant growth of video data over the Internet, video steganography has become a popular choice. The effectiveness of any steganographic algorithm depends on the embedding efficiency, embedding payload, and robustness against attackers. The lack of the preprocessing stage, less security, and low quality of stego videos are the major issues of many existing steganographic methods. The preprocessing stage includes the procedure of manipulating both secret data and cover videos prior to the embedding stage. In this paper, we address these problems by proposing a novel video steganographic method based on Kanade-Lucas-Tomasi (KLT) tracking using Hamming codes (15, 11). The proposed method consists of four main stages: a) the secret message is preprocessed using Hamming codes (15, 11), producing an encoded message, b) face detection and tracking are performed on the cover videos, determining the region of interest (ROI), defined as facial regions, c) the encoded secret message is embedded using an adaptive LSB substitution method in the ROIs of video frames. In each facial pixel 1 LSB, 2 LSBs, 3 LSBs, and 4 LSBs are utilized to embed 3, 6, 9, and 12 bits of the secret message, respectively, and d) the process of extracting the secret message from the RGB color components of the facial regions of stego video is executed. Experimental results demonstrate that the proposed method achieves higher embedding capacity as well as better visual quality of stego videos. Furthermore, the two preprocessing steps increase the security and robustness of the proposed algorithm as compared to state-of-the-art methods.

A video steganography algorithm based on Kanade-Lucas-Tomasi tracking algorithm and error correcting codes

Chaotic systems have been used to generate the substitutional box structures. The existence of endless possibilities for the selection of the initial conditions and control parameters of the chaotic system has made it a necessity to use the optimization algorithms for generation of chaos based substitutional box structures. Most appropriate initial conditions and control parameters have been determined for four different discrete time chaotic systems using seven different optimization algorithms. A new substitutional box generation algorithm has been proposed using the optimum chaotic parameters values parameter values.

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A New Chaotic S-Box Generation Method Using Parameter Optimization of One Dimensional Chaotic Maps

In recent years, experts and scholars in the field of information security have attached great importance to the security of image information. They have proposed many image encryption algorithms with higher security. In order to further improve the security level of image encryption algorithm, this paper proposes a new image encryption algorithm based on two-dimensional Lorenz and Logistic. The encryption test of several classic images proves that the algorithm has high security and strong robustness. This paper also analyzes the security of encryption algorithms, such as analysis of the histogram, entropy process of information, examination of correlation, differential attack, key sensitivity test, secret key space analysis, noise attacks, contrast analysis. By comparing the image encryption algorithm proposed in this paper with some existing image encryption algorithms, the encryption algorithm has the characteristics of large secret key space, sensitivity to the key, small correlation coefficient and high contrast. In addition, the encryption algorithm is used. It can also resist noise attacks.

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Image Encryption Algorithm Based on Logistic and Two-Dimensional Lorenz

In the last two decades, the science of covertly concealing and communicating data has acquired tremendous significance due to the technological advancement in communication and digital content. Steganography is the art of concealing secret data in a particular interactive media transporter, e.g., text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques have become important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of the noteworthy development of advanced video over the Internet. The performance of any steganographic method ultimately relies on the imperceptibility, hiding capacity, and robustness. In the past decade, many video steganography methods have been proposed; however, the literature lacks of sufficient survey articles that discuss all techniques. This paper presents a comprehensive study and analysis of numerous cutting edge video steganography methods and their performance evaluations from literature. Both compressed and raw video steganography methods are surveyed. In the compressed domain, video steganography techniques are categorized according to the video compression stages as venues for data hiding such as intra frame prediction, inter frame prediction, motion vectors, transformed and quantized coefficients, and entropy coding. On the other hand, raw video steganography methods are classified into spatial and transform domains. This survey suggests current research directions and recommendations to improve on existing video steganography techniques.

Compressed and raw video steganography techniques: a comprehensive survey and analysis

This paper focuses on the utilization of digital video/images as cover to hide data. The proposed steganography algorithm based on color histograms for data embedding into Video clips directly, where each pixel in each video frame is divided in two parts, the number of bits which will be embedded in the right part are counted in the left part of the pixel. This algorithm is characterized by the ability of hiding larger size of data and the ability of extracting the written text without errors, besides it gives a high level of authentication to guarantee integrity of the video/ images before being extracted. Furthermore, the data were embedded inside the video/ images randomly which gave the video/ images a higher security and resistance against extraction by attackers.

Hiding data in video sequences using steganography algorithms

In this era of technology, digital images turn out to be ubiquitous in a contemporary society and they can be generated and manipulated by a wide variety of hardware and software technologies. Copy-move forgery is considered as an image tampering technique that aims to generate manipulated tampered images by concealing unwanted objects or reproducing desirable objects within the same image. Therefore, image content authentication has become an essential demand. In this paper, an innovative design for automatic detection of copy-move forgery based on deep learning approaches is proposed. A Convolutional Neural Network (CNN) is specifically designed for Copy-Move Forgery Detection (CMFD). The CNN is exploited to learn hierarchical feature representations from input images, which are used for detecting the tampered and original images. The extensive experiments demonstrate that the proposed deep CMFD algorithm outperforms the traditional CMFD systems by a considerable margin on the three publicly accessible datasets: MICC-F220, MICC-F2000, and MICC-F600. Furthermore, the three datasets are incorporated and joined to the SATs-130 dataset to form new combinations of datasets. An accuracy of 100% has been achieved for the four datasets. This proves the robustness of the proposed algorithm against a diversity of known attacks. For better evaluation, comparative results are included.

A novel deep learning framework for copy-moveforgery detection in images

This paper presents an efficient audio cryptosystem based on combining chaotic maps with optical encryption. The proposed audio cryptosystem is designed with the potential of enforcing the security level for digital speech communication via shared networks. The proposed audio cryptosystem is built using two security phases. In the first phase, it utilizes a chaotic system using either Baker map or cat map for providing the first security level. In the second phase, it utilizes optical encryption using double random phase encoding (DRPE) for providing the second security level. This second security level represented with DRPE is a physical security that is very hard to attack. The proposed audio cryptosystem is implemented and its performance is evaluated using different audio encryption/decryption quality metrics. The results demonstrated that the proposed audio cryptosystem increases the level of voice security with high degree of confidentiality.

Efficient audio cryptosystem based on chaotic maps and double random phase encoding

Digital images and their applications gained a huge interest around the world in several fields like newspapers, social media, defaming persons, and courts. There are two types of digital image authentication. The first type is active authentication, which uses digital signature and image watermarks. These techniques have certain constraints such as knowing the content of the digital image. They need special equipment like cameras and development software. The second type is passive authentication, which is used to detect digital image forgeries represented in image cloning, image splicing, image resampling, image retouching, and image morphing. Passive authentication has an advantage of not needing any previous knowledge of the image content to detect the forgery. Copy-move forgery is the most famous type, and it is widespread in all image forgeries. Copy-move forgery is easy to perform and the forged part has the same properties of the whole image that makes it difficult to detect. There are many algorithms used to detect copy-move forgery attacks depending on different techniques. This paper covers the directions of copy-move forgery detection and gives a wide coverage of earlier copy-move forgery detection algorithms and techniques.

Comparative study of copy-move forgery detection techniques

This paper demonstrates an image encryption technique using a hybrid method. This method consists of two stages. The image is XORed with the Pseudo-Random Number Generator (PRNG) in the first stage. The confusion and diffusion processes are applied by using the Logistic map and its’ three modifications in the second stage. The original Logistic map has a small range of key-space. The three modifications of Logistic map increased key-space range due to expanding the range of the original Logistic map parameter. Multiple tests have been performed on the hybrid method such as security analysis and encryption quality. The hybrid method presented a good evaluation.

Osama A. Elshakankiry

Papers

Hiding data in video sequences using steganography algorithms

A novel deep learning framework for copy-moveforgery detection in images

Efficient audio cryptosystem based on chaotic maps and double random phase encoding

Comparative study of copy-move forgery detection techniques

A fast hybrid image cryptosystem based on random generator and modified logistic map