Low-cost multiclass-image encryption based on compressive sensing and chaotic system

In this paper, a compressible and low-cost cryptography system is investigated based a new memristor system for Internet of multimedia things to acquire and transmit multiclass-image signals, such as grayscale, color and 3D images (Stereolithography format). Compression sensing is first introduced to solve the limitation of computing and storage resources faced by detectors when sampling data from different scenarios. The batch data after sampling are fused into 3D cubes, and the confusion–diffusion framework is used to encrypt them in 3D space to ensure the privacy of information during transmission. For confusion procedure, a novel technique, like 3D jigsaw puzzles, is designed to improve the efficiency of scrambling. Furthermore, a new nonlinear primitive is proposed based on three-input majority gate , and the non-sequential diffusion path generated by depth-first search is used for diffusion operation. The experimental results and extensive security analysis show that the proposed encryption technique combined with the implementation of 3D space significantly improves the security and efficiency of batch image processing.