Audio Steganography Implementation Using MATLAB and Discrete Cosine Transform

This document presents a comprehensive implementation of audio steganography using MATLAB, focusing on the technique of concealing secret information within digital audio signals. Steganography involves embedding files, messages, or data within carrier media like audio files to protect sensitive information from unauthorized access. Audio steganography represents a specialized branch of digital forensics that enables hidden data embedding in audio files, particularly valuable for investigative applications involving audio recordings. The implementation employs Discrete Cosine Transform (DCT) as the core mathematical framework for frequency-domain analysis. The DCT-based approach converts audio signals into frequency components through MATLAB's dct() function, allowing identification of optimal frequency bands for data embedding. Key implementation steps include: 1. Audio signal preprocessing using audioread() for input handling and normalization 2. Frame-based processing with buffer() function for segmenting audio into manageable blocks 3. DCT coefficient calculation and quantization for frequency component manipulation 4. Bit-plane modification in mid-frequency DCT coefficients using logical operations for data embedding 5. Inverse DCT transformation via idct() function to reconstruct the stego-audio signal The algorithm ensures minimal perceptual distortion by modifying less sensitive frequency components, maintaining audio quality while embedding payload data. MATLAB functions like audiowrite() handle output generation, while error-checking mechanisms validate embedding capacity and signal integrity. Audio steganography constitutes a critical discipline in digital signal processing with extensive applications in security and forensics. Understanding these implementation techniques enables robust protection of sensitive information through advanced audio data hiding methodologies.