Audio Steganography for Healthcare Data Using 24x8 Compression and Bit Comparison Substitution Algorithm
Abstract
Audio steganography embeds multimedia files within audio files. Traditional audio steganography used the Least Significant Bit algorithm, which required eight samples to embed one byte of a text file. This study reduces the utilization of audio samples by compressing healthcare data from three characters to one using the proposed 24×8 compression algorithm. Three audio files were used to transmit the probability distributions, encoded values, and index values. The encoded values are embedded using the Bit Comparison and Substitution-3 algorithm, with a three-bit difference from audio samples. It is retrieved using the Bit Comparison and Retrieval-3 algorithm and decompressed with the 8×24 decompression algorithm. For enhanced security, healthcare data was encrypted using the Incremental Order Value Algorithm and decrypted with the Decremental Reverse Order Value Algorithm. The least significant bit algorithm embeds the probability distributions and index values with a secret key. Audio files from Mixkit and healthcare data from the COVID Dialogue Dataset were used for evaluation. The proposed algorithms achieved an average throughput of 8592.74 KB/s, surpassing the 3-DES algorithm due to the incremental shift in ASCII values within healthcare data. A compression ratio of 3:1 was achieved by compressing 3 bytes of data to 1, outperforming Huffman and LZW. The embedding algorithm achieved a PSNR of 42.1480 dB and a BER of 7.0165 × 10⁻⁵, demonstrating improved efficiency with reduced audio samples in embedding compared to the traditional LSB algorithm. 15000 bytes of healthcare data were embedded into 5000 audio samples, resulting in 15000-bit differences between the cover and stego audio files.References
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