Reversible Data Hiding In Encrypted Image With High Significant Bit Plane Redundancy Compression

With the development of computer technology,more and more people are storing their own data in the cloud.However,data stored in the cloud is highly likely to reveal its privacy without being encrypted.Images as the most commonly used digital media in life need to be protected.The reversible data hiding technology in the encrypted image can be widely used to realize the privacy protection and convenient management of cloud storage images,and has become a research hotspot.The existing reversible data hiding in the encrypted domain before vacating space does not fully utilize the correlation of natural images.Therefore,this thesis focuses on reducing the bit-plane redundancy of images according to the correlation between bit-planes of natural images.Two reversible data hiding algorithms in the encryption domain based on vacating room before encryption are proposed.The main work of this paper has the following aspects:1)Three RDH-EI algorithms that make use of the correlation of natural images to make space are introduced.The characteristics of natural images are analyzed by mathematical statistics.On this basis,the advantages and disadvantages of the three methods in vacating room are summarized.The method based on prediction error histogram translation is simple and fast,but the data embedded in this method is the least compared to the other two methods;the method based on MSB-flipped prediction makes the redundancy and information entropy of the predicted highest bit plane close to the optimal value,which is more conducive to the compression,and the maximum embedding rate can reach about 1 bpp.The MSB-flipped prediction has a prediction accuracy of nearly 100% for a smoother texture image,and can achieve an embedding rate of about 1 bpp;the bit-plane compression algorithms compresse multiple bit-planes.This method has the highest embedding rate compared to the other two methods.Based on the above analysis,we have proposed two VRBE-based RDH-EI algorithms.2)An RDH-EI algorithm that reduces the redundancy between adjacent bit planes is proposed by analyzing the statistical characteristics between adjacent bit-planes.This characteristic is that the probability of opposite bits in the adjacent high significant bit-plane can reach 70.1%.The algorithm has a positive influence on the redundancy and the representation of information entropy after encoding the adjacent bit planes,that is,the bit plane becomes smoother.After the adjacent bit-planes are encoded,the bit-planes have a positive effect on both redundancy and information entropy,that is,the bit-plane becomes smoother.On this basis,we use BBE to free up more space.Block scrambling and bitwise XOR encryption used in the encryption phase provide high security.The experimental results show that the algorithm can achieve true reversibility.Compared with the existing algorithms based on bit-plane compression,the proposed algorithm has higher embedding capacity(the Lena image can reach 2.35 bpp).3)An RDH-EI algorithm based on prediction and compression coding is proposed.First,the multiple high siginificant bit-planes of the original image need to be processed for prediction.The redundancy and information entropy of the predicted bit-planes are close to the optimal value.The distribution of the same pixel values in the processed bit-planes are concentrated,which facilitate compression by blocking.Then,the predicted adjacent bit-planes are subjected to exclusive-xor coding,which further increases the redundancy of the bit-planes.In order to ensure the security of the encrypted images,the compressed bit stream is encrypted by a scrambling-exclusive combination encryption method.The receiver can obtain the restored image that is consistent with the original image only by the encryption key.The experimental results show that the algorithm achieves a high embedding rate(the Lena image can reach 2.59 bpp).In addition,the proposed algorithm can adaptively generate the encrypted images with a small file-size according to the amount of data to be embedded.The file-size of the encrypted images can be reduced to 40% ~ 91% of the original image.