# Data Hiding and Authentication Scheme for Medical Images Using Double POB
## 1 Introduction
[11; 12] proposed a technique to detect and locate the tampered area, which also has the ability to recover tampering by embedding authentication bits into each block's three LSBs, and recovery bits are attached to mapping blocks; this technique restores the tampered area with 50% accuracy. [PERSON] et al. [13] use two watermarking methods to detect and locate real-time tampering in medical images and other common images. A highly efficient fragile watermarking strategy was proposed by [PERSON] et al. [14]. A fragile watermarking technique was proposed by [PERSON] et al. [15], who replaced an image's LSB with authentication and self-recovery bits in order to identify tampering and recover tampered regions. [PERSON] et al. [16] used fragile watermarks and block checksums to detect and locate tampering. Additionally, in [17], [PERSON] et al. improved ROI contrast without adding distortion and used it for tamper detection. The permutation ordered binary (POB) number system was introduced recently by [PERSON] et al. [18], aiming to construct a novel secret sharing method. It is applied to medical images to enhance security and protect the integrity of medical images. Compared with some existing algorithms, the POB number system has been further developed and applied in tamper detection, lossless recovery, bit plane compression, and so on. [PERSON] et al. [19] tried to use POB as a solution for re-encrypting the contents of the image during the data hiding process, but this scheme had a low embedding capacity. Using a POB number system on a cloud server, [PERSON] and [PERSON] [20; 21] presented a safe method for detecting and recovering from image tampering. [PERSON] et al. [22] used image tamper detection and lossless recovery, combined with POB digital system to perform neighborhood refinement and watermark refinement. The results of the experiment demonstrated that, under some circumstances, the method performed well, but there were still some problems in recovering large-scale tampering. To solve such problems, [PERSON] et al. [23] proposed a scheme for medical image authentication recovery based on the POB algorithm. Experimental findings and theoretical research have demonstrated that this strategy allowsthe lossless recovery of original images under different tampering attacks, but this scheme can only achieve simple authentication and still has defects in carrying additional data. Targeting the aforementioned inadequacies, this research proposes a medical image hiding and authentication algorithm based on double POB system. The scheme not only realizes the authentication of the medical image but can also transmit additional secret data during the authentication. Firstly, the region of significance (ROS) part of the original medical image is separated into an ROI and an RONI by a segmentation algorithm, and then these two regions are separated and cross-reorganized to generate two shares so as to prevent the high-bit sensitive pixels in the ROI from being tampered with. Then, the two Share images were compressed, and the compressed data were repeatedly placed in the plane with the same size as the original image; then, the plane was encrypted using a hyperchaotic Lorenz system. Finally, the double POB number system was used to complete the data hiding and authentication. After successful authentication, the embedded secret message is extracted, and the original medical image is recovered. If the data are tampered with, the original image can still be recovered completely by repeating the data placement. The primary contributions of this research are summarized as follows:  
1. We utilized a double POB digital system to simultaneously achieve data hiding and the authentication of medical images. The embedding capacity of data hiding is large, and the process is reversible; the authentication is based on the pixel level, which is very sensitive to any small tampering and meets the needs of medical images. 2.