Data-Loss resilience video steganography using frame reference and data ensemble reconstruction.

Area of Science:

• Computer Science
• Information Security
• Digital Forensics

Background:

• Steganography is crucial for covert communication.
• Existing video steganographic methods face challenges in minimizing distortion and maintaining robustness against frame loss.
• Securely embedding and retrieving hidden data in video sequences remains a significant research problem.

Purpose of the Study:

• To propose a robust video steganographic method for efficient and secure message hiding.
• To address the challenges of minimizing steganographic distortion in video frames.
• To ensure perfect reconstruction of hidden messages, even when video frames are lost or damaged.

Main Methods:

• A novel distortion function is designed using adjacent frames as side-information to minimize embedding distortion.
• Data sharing, utilizing a multi-ary Vandermonde matrix, is employed for data redundancy and recovery.
• The method ensures hidden messages can be reconstructed despite frame loss or damage.

Main Results:

• The proposed method effectively minimizes steganographic distortion per video frame.
• Data redundancy through data sharing enables robust recovery of hidden messages.
• Experimental results demonstrate superior performance compared to state-of-the-art methods against various attacks.

Conclusions:

• The developed video steganographic method offers high robustness and efficiency.
• The technique provides a reliable solution for secure data embedding and retrieval in video sequences.
• This approach significantly advances the field of robust video steganography.