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.

Development and optimization of a method for analysis of the products from the transesterification of dimethyl carbonate and phenol.

A high-purity sample of methyl phenyl carbonate (MPC) was obtained by developing a novel reaction route followed by a series of separation and purification procedures. Identification and quantification of the MPC sample (98.32%) was performed by a gas chromatography-mass spectrometry and Karl Fisher titration. The laboratory-prepared MPC was then used as a standard to optimize quantitative analysis of the products synthesized by transesterification of dimethyl carbonate and phenol. The advantage of the improved method was that MPC can be quantified directly rather than being calculated by subtracting the yield of diphenyl carbonate (DPC) and by-product anisole from the conversion of dimethyl carbonate (DMC). The resulting method was validated for linearity, precision, accuracy, detection limit, and quantification limit. With the improved method, simultaneous accurate quantification of DMC, MPC, DPC, phenol, and anisole in the transesterification products can be achieved. This enables evaluation of the activity and selectivity of different catalysts and control of the reaction processes.