Reversible data hiding in encrypted images based on additive homomorphic encryption and multi-MSB embedding - Wenqian XIAO, Gaobo YANG, Dewang WANG, Ming XIA (网络与信息安全学报, 2023)
Reversible Data Hiding in Encrypted Images (RDHEI) combines image encryption and reversible data hiding to improve the security and information transmission efficiency for the network transmission of images.In RDHEI, the conventional bit-by-bit encryption destroys the spatial correlation in an original image and has side effects on the preservation of embedding spaces.An approach for RHDEI was proposed, which utilized additive homomorphic encryption and a multi-MSB (Most Significant Bit) embedding strategy to create room within the encryption process.The original image was divided into non-overlapped blocks, and each block was subjected to the same key for additive homomorphic encryption.This helped transfer the pixel correlation within an original block to the encrypted image block as much as possible.To enhance security, the encrypted image was further subjected to an Arnold transformation on a block-by-block basis.The decision of whether data will be embedded in a block and the embedding capacity were determined by the pixel differences within the block and the predicted values.When a block was selected for embedding, a small number of LSBs (Least Significant Bits) were used to store the prediction differences, ensuring reversibility.The redundant multi-MSBs were embedded with secret information by bit replacement.For the possible errors caused by multi-MSBs prediction, an embedding position selection strategy was designed by vacating MSBs in terms of the values of prediction errors, then more MSBs were reserved for those pixels with less prediction errors.During decryption, the secret information can be accurately extracted from the multiple MSBs of the pixels in a block, and the image content can be losslessly recovered using the number of embedded multi-MSBs, predicted values, and prediction differences.Experimental results on the BOWS-2 image dataset demonstrate that the average embedding capacity is improved to 2.58 bit/pixel, surpassing existing methods.