Research On High-payload Reversible Data Hiding In Encrypted Images

With the rapid development of Internet technology,the frequency of people uploading private information to the cloud continues to increase.Cloud storage technology brings convenience to people,but also has great security risks.More and more users encrypt their personal information to protect it before uploading it to the cloud.Reversible data hiding in encrypted images(RDHEI)can embed secret data into encrypted images,and images can be recovered without error after extracting embedded information.It can be used to manage,annotate,and authenticate encrypted images.Therefore,RDHEI has attracted the attention of numerous researchers both domestically and internationally.Under the premise of ensuring the reversibility of the RDHEI method,this project proposes two high-capacity RDHEI methods with the research goal of improving the security of encrypted images and data embedding capacity.The main contents are summarized as follows.(1)RDHEI method based on block capacity label(BCL)is proposed.Firstly,the image is preprocessed and divided into reference pixel regions and predicted pixel regions.The median edge detector(MED)algorithm is used to calculate the prediction error of pixels in the predicted pixel regions,and then the predicted pixel regions is divided into blocks.Next,based on the BCL algorithm,the embedding capacity of all blocks is marked,and after encrypting the image,the BCL is embedded in the encrypted image.Finally,secret data is embedded into the encrypted image based on BCL.The experimental results show that this method improves the data embedding capacity and can achieve perfect reconstruction of the original image.In addition,the image security is improved by using a two-layer encryption mechanism consisting of block scrambling and a stream cipher.(2)RDHEI method based on Kd-tree and entropy coding is proposed.First of all,MED algorithm is used to calculate the prediction error of pixels,and then the image is divided into two regions for processing through using two algorithms respectively.The four most significant bit(MSB)planes use the Kd-tree marking algorithm to mark the redundant space,and entropy encoding compression is performed on each of the four least significant bit(LSB)planes.Then the corresponding auxiliary information is generated.The data embedder embeds secret data in the redundant space of the encrypted image through the retrieval of auxiliary information.The experimental results show that the method further improves the data hiding capacity.(3)A GUI simulation system is designed using the two RDHEI frameworks proposed in this project,which intuitively verified the effectiveness of the method.