A fine-grained reversible data hiding in encrypted domain based on the cipher-text redundancy of encryption process

Considering the granularity of embedded data in the design of reversible data hiding scheme has important research significance for the permission control and management of multi-granularity information. To broaden the application possibilities of encrypted data in cloud environments, the researchers propose a fine-grained reversible data hiding method leveraging the cipher-text redundancy of ElGamal encryption. Initially, prior to the encryption process, pixels are organized into a full binary tree based on fine-grained access permissions. Subsequently, a chaotic sequence generator is employed to assign distinct embedding keys to each layer of the full binary tree according to the access permissions. Following this, an XOR operation is conducted between the embedding key and the corresponding secret information in each layer to derive the target features of the cipher-text, facilitating subsequent fine-grained data hiding. Throughout the ElGamal encryption process, iterative manipulation of the random variable ensures alignment between the cipher-text output and the target feature, enabling the embedding of secret information across different layers. This approach facilitates the fine-grained blind extraction of secret information from an encrypted state, thereby expanding the potential applications of cipher-text by extracting information without revealing the original data. Furthermore, the scheme enhances information security through distributed storage and conceals the presence of information hiding by leveraging the separability of lossless decryption and information extraction. Simulation results demonstrate that secret information of three granularities can be embedded and extracted without interference within a three-layer full binary structure, with a maximum embedding capacity of up to 1.75 bpp.