A novel image cryptosystem using Gray code, quantum walks, and Henon map for cloud applications

Efficient S-box construction based on quantum-inspired quantum walks with PSO algorithm and its application to image cryptosystem

Amidst the growth of the internet and communication technologies, the requirements for the security of data transmitted via these technologies are increasing. Visual data, like images and videos, are commonly utilized for representing the majority of data due to its having more detailed information. Until now, the physical implementation of quantum computers does not have enough capability for hacking any traditional image cryptosystem, but amidst the growth of quantum resources, enough capability may be available in the near future. Most data represented by images has a long lifetime, like personal, medical, military, etc. Therefore, new quantum-inspired-based designs for image cryptosystems are required to be performed on digital resources and have the capability of defying the potential attacks from digital and quantum resources. In this study, a new substitution box (S-box) mechanism is proposed, which is based on quantum-inspired quantum walks, Hénon map, and a customized particle swarm optimization algorithm. Performance analysis of the suggested S-box proves its effectiveness and its reliability in designing various cryptosystems. Based on the effectiveness of the presented S-box, a new image cryptosystem is proposed, in which its experiential outcomes prove its efficacy and security against various attacks. The average outcome of entropy is 7.99977, UACI is 33.484%, NPCR is 99.618%, and Chi-square is 249.481 for the constructed cipher images.

A robust medical image steganography approach based on particle swarm optimization algorithm and quantum walks

Medical information plays an essential task in our everyday lives, in which medical data privacy and security constitute an important issue. The confidentiality of medical data can be achieved by applying one or more encryption and data hiding methods. Amidst the development of quantum computers, most medical data confidentiality techniques may be hacked because their construction is based on mathematical models. Most medical data have a long lifetime exceeding 25 years. Therefore, it is an important issue to design a new medical data hiding technique that has the capability to withstand the probable attacks from the side of quantum or digital devices. In this article, we aim to present a novel medical image steganography strategy based on quantum walks, chaotic systems, and particle swarm optimization algorithm. A 3-D chaotic system and quantum walks are utilized for operating particle swarm optimization algorithm, in which the generated velocity sequence is utilized for substituting the confidential data, and the position sequence is utilized for selecting which position in the hosting image will be employed to host the substituted confidential data. The payload capacity of the suggested mechanism is 2 bits per 1 byte, and the average value for PSNR is 44.1, which is big enough for the naked eye to not differentiate the difference between the carrier image and its stego one.