2차원 혼돈 함수와 C-MLCA를 이용한 컬러 의료 영상 암호화 방식

Abstract

With the rapid change of the digital age, the number of digital medical devices used in the medical industry is increasing. The introduction of PACS (Picture Archiving and Communication System) also made editing, searching, viewing, and sending of medical images much easier. However, as various problems arise in the information age; data modification and copying, digital medical images are also exposed to problems such as illegal information leakage and the infringement of patient’s privacy due to the theft. Among various encryption methods, this paper attempts to encrypt images using two-dimensional chaotic map and C-MLCA (Complemented Maximum Length Cellular Automata). The two-dimensional chaotic map encrypts the image by moving the position of the pixel. Then, C-MLCA encrypts the image by changing the eigenvalues ​​of the pixels through the computation process. Using these two features, we will introduce an effective encryption method to overcome the limitations of the existing encryption methods. The new encryption method introduced in this paper is as follows. First, we generate a state transition matrix T1 and T2 using a Wolfram rule, and create a PN (Pseudo Noise) sequence of maximum length. By XORing the complemented vector, it converts an existing sequence to a more complex sequence Then, we multiply the two sequences by rows and columns to generate various basis images of the original image size. Each of the C-MLCA basis images is XOR-computed by red frame, green frame and blue frame of the original medical image. Finally, we perform a conversion process using a two-dimensional chaotic map to produce a more robust encrypted image. By comparing and analyzing the encrypted image with the original image, we were able to confirm that the proposed encryption method has a high level of stability and security. By analyzing the histogram and PSNR, we confirmed that this encryption method has been successfully performed. Also, by analyzing correlation coefficient, SSIM, entropy and NPCR, we confirmed how secure the encrypted image is from external attacks.