AI-Driven Image-to-Audio Encryption with Data Hiding
Anjali Chennupati, Bhamidipati Prahas, Bharadwaj Aaditya Ghali, T.V Nidhin Prabhakar · 2024
The proposed framework addresses the critical need for secure multimedia data sharing by integrating image-to-audio encryption with advanced AI-based data-hiding techniques. The core concept involves transforming static visual content into dynamic auditory experiences, injecting semantic depth and artistic creativity into the resulting audio output. Unlike conventional methods, this approach goes beyond translating pixels into sound waves. It holds promise in multimedia communication, artistic expression, and data protection. To enhance security, this framework introduces AIenhanced data-hiding techniques, leveraging adversarial training and reinforcement learning. This extra layer ensures resistance to unauthorized access and tampering. In summary, this approach fuses image-to-audio encryption and AI-enhanced data hiding, aiming to revolutionize multimedia, thus offering a robust solution, transcending boundaries by safeguarding visual data through the immersive medium of audio.