Selective bin model for reversible data hiding in encrypted images

• Published in: Pattern analysis and applications : PAA Vol. 27; no. 1
• Main Authors: Agarwal, Ruchi, Ahmed, Sara, Kumar, Manoj
• Format: Journal Article
• Language: English
• Published: London Springer London 01.03.2024; Springer Nature B.V
• Subjects: Bins; Communication; Computer Science; Data transmission; Digital imaging; Embedding; Encryption; Image compression; Image enhancement; Pattern Recognition; Theoretical Advances; Information Security; Selective Bin Model; Secure Communication; Lossless Compression; Data Hiding
• ISSN: 1433-7541; 1433-755X
• DOI: 10.1007/s10044-024-01220-z

In tandem with the fast-growing technology, the issue of secure data transmission over the Internet has achieved increasing importance. In digital media, enclosing data in images is one of the most common methods for communicating confidential information. A novel reversible data hiding in the encrypted images scheme based on selective bin models is proposed in this paper. The scheme focuses on enhancing the embedding capacity while ensuring the security of images with the help of encryption and the proposed data hiding process. For data embedding, lossless compression is utilized and the image is classified into three bins. Then, marker bits are assigned to these bins for distinguishing between embeddable and non-embeddable regions. The proposed method shows a satisfactory embedding rate for smooth images as well as complex ones due to its selective bin approach. Also, the method is separable in nature, i.e., data extraction and image recovery can be performed independently. Furthermore, the experimental results demonstrate the strategy’s effectiveness when compared with others.