Interpolation-Based Reversible Data Hiding in Encrypted Audio with Scalable Embedding Capacity

With the rapid expansion of multimedia data, protecting digital information has become increasingly critical. Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction. Audio, as a vital medium in communication, entertainment, and information sharing, demands the same level of security as images. However, embedding data in encrypted audio poses unique challenges due to the trade-offs between security, data integrity, and embedding capacity. This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity. By increasing sample density through interpolation, embedding opportunities are significantly enhanced while maintaining encryption throughout the process. The method further integrates multiple most significant bit (multi-MSB) prediction and Huffman coding to optimize compression and embedding efficiency. Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity, while preserving full reversibility. These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio. This work advances reversible data hiding in encrypted audio by offering a secure, efficient, and fully reversible data hiding framework.