Image Encryption and Stegenography Based on Computational Single Pixel Imaging

Multiple layers of information security are introduced based on computational ghost imaging (CGI). We show, in the first step, that it is possible to design a very reliable image encryption scheme using 3D computational ghost imaging with two single-pixel detectors sending data through two channels. Through the Normalized Root Mean Square scale, it is then shown that a further level of security can be achieved by merging data-carrying channels into one and using a coded order for their placement in the sequence of bucket data carried by the single channel. Yet another layer of security is introduced through hiding the actual grayscale image inside another image such that the hidden image cannot be recognized by naked eyes. We then retrieve the hidden image from a CGI reconstructed image. It is shown that the proposed scheme increases the security and robustness such that an attacker needs more than 96 percent of the coded order to recover the hidden data. Storing a grayscale image in a ghost image and retrieving different intensities for the hidden image is unprecedented and could be of interest to the information security community

A Secure and Lightweight Chaos Based Image Encryption Scheme

In this paper, we present an image encryption scheme based on the multi-stage chaos-based image encryption algorithm. The method works on the principle of confusion and diffusion. The proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing schemes. Initially, an image (red, green, and blue components) is partitioned into blocks with an equal number of pixels. Each block is then processed with Tinkerbell Chaotic Map (TBCM) to get shuffled pixels and shuffled blocks. Composite Fractal Function (CFF) change the value of pixels of each color component (layer) to obtain a random sequence. Through the obtained random sequence, three layers of plain image are encrypted. Finally, with each encrypted layer, Brownian Particles (BP) are XORed that added an extra layer of security. The experimental tests including a number of statistical tests validated the security of the presented scheme. The results reported in the paper show that the proposed scheme has higher security and is lightweight as compared to state-of-the-art methods proposed in the literature

A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map

Chaos-based encryption schemes have attracted many researchers around the world in the digital image security domain. Digital images can be secured using existing chaotic maps, multiple chaotic maps, and several other hybrid dynamic systems that enhance the non-linearity of digital images. The combined property of confusion and diffusion was introduced by Claude Shannon which can be employed for digital image security. In this paper, we proposed a novel system that is computationally less expensive and provided a higher level of security. The system is based on a shuffling process with fractals key along with three-dimensional Lorenz chaotic map. The shuffling process added the confusion property and the pixels of the standard image is shuffled. Three-dimensional Lorenz chaotic map is used for a diffusion process which distorted all pixels of the image. In the statistical security test, means square error (MSE) evaluated error value was greater than the average value of 10000 for all standard images. The value of peak signal to noise (PSNR) was 7.69(dB) for the test image. Moreover, the calculated correlation coefficient values for each direction of the encrypted images was less than zero with a number of pixel change rate (NPCR) higher than 99%. During the security test, the entropy values were more than 7.9 for each grey channel which is almost equal to the ideal value of 8 for an 8-bit system. Numerous security tests and low computational complexity tests validate the security, robustness, and real-time implementation of the presented scheme