In the most existing reversible data hiding schemes for encrypted images, cover images can be reversibly recovered, but the integrity of image content cannot be guaranteed. This paper proposes a reversible data hiding and authentication scheme for encrypted images to implement reversible recovery and content authentication of cover images and secret data. The content owner employs a new predictor ISGAP to generate more accurate predictions and smaller errors. The errors are then compressed with adaptive Huffman coding to enlarge the embedding space, and the plaintext authentication information is embedded in it. The data hider embeds secret data into the encrypted image along with ciphertext authentication information. The receiver performs ciphertext authentication first and then implements cover recovery and plaintext authentication according to different keys. Experiments were carried out with 100 images selected from each dataset of BOSSbase and BOWS-2, and the results show that the scheme has higher embedding capacity and can effectively implement image content authentication while ensuring high security and reversible recovery.

The security vulnerability of space information network is stimulating interest in developing security mechanisms study of heterogeneous network. However, it is noted that neither the single certificate authority (CA) nor the distributed CA can meet the security requirements for this type of network. In this study, the authors propose an adaptive distributed certificate management scheme in which the nodes that provide certificate services are selected dynamically in the network. The security risks caused by the static nodes are avoided in the proposed scheme. The status of the nodes in the network is completely equal and the credit values that vary with the operation of the network are the only criterion to measure their responsibilities. The scheme can effectively prevent attackers from getting permission of the certificate services and could be applicable to the complex and dynamic networks.

To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which includes three parts: image preprocessing, double hiding, and information extraction and lossless recovery. In the image preprocessing and double hiding phase, firstly, the region of significance (ROS) of the original medical image is segmented into a region of interest (ROI) and a region of non-interest (RONI). Then, the bit plane of the ROI and RONI are separated and cross-reorganization to obtain two new Share images. After the two new Share images are compressed, the images are encrypted to generate two encrypted shares. Finally, the embedding of secret data and attaching of authentication bits in each of these two encrypted shares was performed using the POB algorithm. In the information extraction and lossless recovery phase, the POBN algorithm is first used to extract the authentication bits to realize image tamper detection; then, the embedded secret message is extracted, and the original medical image is recovered. The method proposed in this research performs better in data embedding and lossless recovery, as demonstrated by experiments.

In this paper, we propose a reversible data hiding scheme in an encrypted image based on bit-plane redundancy of prediction error. The scheme greatly improves the embedding capacity while maintaining lossless image recovery and error-free secret data extraction. Firstly, the original image is preprocessed to obtain the prediction error image. After the error matrix is divided into blocks, the corresponding block type is obtained. Secondly, the predicted error image is encrypted with stream cipher and the encryption matrix blocks are scrambled to ensure the security of the scheme. Finally, after embedding the block type value into the encrypted image, the spare room corresponding to each block was obtained, which was used to embed the secret data. The scheme makes full use of the spatial correlation of the pixels in the block, so it improves the embedding rate. By selecting 100 images in each dataset of BOSSbase and BOWS-2, when the block size is $3\times 3$, the average embedding rate of our scheme can reach 3.56 bpp and 3.81 bpp, respectively. The performance of the proposed method is better than the other schemes with similar properties.