A new four-dimensional hyper-chaotic system for image encryption

Currently, images are very important with the rapid growth of communication networks. Therefore, image encryption is a process to provide security for private information and prevent unwanted access to sensitive data by unauthorized individuals. Chaos systems provide an important role for key generation, with high randomization properties and accurate performance. In this study, a new four-dimensional hyper-chaotic system has been suggested that is used in the keys generation, which are utilized in the image encryption process to achieve permutation and substitution operations. Firstly, color bands are permuted using the index of the chaotic sequences to remove the high correlation among neighboring pixels. Secondly, dynamic S-boxes achieve the principle of substitution, which are utilized to diffuse the pixel values of the color image. The efficiency of the proposed method is tested by the key space, histogram, and so on. Security analysis shows that the proposed method for encrypting images is secure and resistant to different attacks. It contains a big key space of (2627) and a high sensitivity to a slight change in the secret key, a fairly uniform histogram, and entropy values nearby to the best value of 8. Moreover, it consumes a very short time for encryption and decryption

Quad-color image encryption based on Chaos and Fibonacci Q-matrix

The Information technology requires the transmission of daily-life images that may reach to millions or even more. Thus, securing them becomes an urgent matter using the encryption technique. Where, a secret key is used for converting the original image into a noisy one and restoring it back using the same key. Confusion and Diffusion are the wildly used steps in such a technique. Therefore, a new algorithm is presented in this work that uses a fusion, segmentation, random assembling, hyperchaotic and Fibonacci Q-matrix (FQ-matrix). A novel fusion method is designed for fusing four color images into four different sequences according to their contained information. Then the resulted four images are each divided into four segments to be assembled randomly into one image using a random-key; which confused later using a six-dimensional hyperchaotic system and diffused using the FQ-matrix. The performance and robustness of the proposed algorithm have been computed based on different tests; where it proved its powerful capability in securing the transmitted images

Steganography Using Stochastic Diffusion for the Covert Communication of Digital Images

This paper is devoted to the study of a method called Stochastic Diffusion for encrypting digital images and embedding the information in another host image or image set. We introduce the theoretical background to the method and the mathematical models upon which it is based. This includes a comprehensive study of the diffusion equation and its properties leading to a convolution model for encrypting data with a stochastic field that is fundamental to the approach considered. Two methods of implementing the approach are then considered. The first method introduces a lossy algorithm for hiding an image in a single host image which is based on the binarization of the encrypted data. The second method considers a similar approach which uses three host images to produce a near perfect reconstruction from the decrypt. In both cases, details of the algorithms developed are provide and examples given. The methods considered have applications for covert cryptography and the authentication and self-authentication of documents and full colour images

Visual Privacy Protection Methods: A Survey

Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual’s privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users’ acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people’s privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U - A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649). José Ramón Padilla López and Alexandros Andre Chaaraoui acknowledge financial support by the Conselleria d'Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2012/064 and ACIF/2011/160 respectively)

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future