Selective region medical image encryption algorithm based on cascade chaos and two-dimensional Joseph traversal

Abstract

Aiming at the problem that medical image information is easy to be stolen, tampered and maliciously destroyed in the transmission process, a selective region medical image encryption algorithm based on cascade chaos is proposed. The encryption algorithm consists of two stages: region of interest (ROI) encryption and full image encryption. First, the Cubic map is cascaded with an improved Cosine map. Through the analysis of dynamic characteristics, the cascade map has better chaotic performance than the traditional chaotic systems. The key sequence is generated by the cascade map and the image. Then edge detection is performed on the image to determine ROI. ROI is divided into multiple image blocks, and a new gradient algorithm is used to label the sub-blocks containing important information. A modified two-dimensional Joseph traversal method is used to scramble the positions of pixels in each sub-block, and further modify their pixel values with a round of diffusion. Finally, we use a block V-shape scrambling method to scramble the entire image. The final encrypted image is obtained through a round of bidirectional diffusion of all pixels using chaotic sequences. Simulation results and security analysis show that the algorithm has large key space and sufficient security. It can effectively resist various malicious attacks.

Visually secure traffic image encryption scheme using new two-dimensional Sigmoid-type memristive chaotic map and Laguerre transform embedding

“…where f i and g i represents the actual and theoretical probability of appearance, respectively. For images of gray level 256, we set the significance level as 0.05 under c c < 2 0.05 2 implies that they pass the chi-square test [36]. In table 6, the data illustrates that they all passed the chi-square test, further proving that the histograms of the secret images were uniformly distributed.…”

Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

“…Gao et al [16] developed a hyperchaotic map by employing a discrete resistance-coupled sinusoidal map and further enhancing the algorithm's complexity by introducing DNA mutation. Chen et al [17] combined a cubic map with an improved cosine map to realize a selective regional medical image encryption algorithm. However, this algorithm lacks a significant advantage in terms of time efficiency, posing challenges in achieving realtime encryption.…”

Multi-Objective Region Encryption Algorithm Based on Adaptive Mechanism

“…Encrypting the entire image largely wastes resources. Therefore, in recent years, there has been a growing number of encryption algorithms focusing on regions of interest in images [18][19][20][21]. Liu [22] proposed a method where the content owner divides the image into regions of interest and non-interest.…”