Metadata-Based Video Steganography: Development of a New Model for Secure Information Embedding
Dedi Darwis, Yusra Fernando, Abhishek R. Mehta, Wamiliana Wamiliana, Setiawansyah Setiawansyah · Engineering Technology & Applied Science Research · 2025
This study introduces a novel video steganography model called Video Steganography Technique in Metadata (VSTM), which embeds secret messages within the metadata of MP4 video files. By utilizing the 'comments' field in the metadata, the method ensures that the visual and audio quality of the video remains unaffected. This model offers original contributions in maintaining the integrity and resilience of digital data against common manipulations, such as cropping, rotation, and social media compression. The VSTM model combines the Advanced Encryption Standard (AES) for encryption and ZLIB for data compression, enhancing the security and optimizing the data size. The tests demonstrate that the VSTM model maintains perfect video fidelity with no detectable pixel changes and achieves a high level of robustness against various manipulations, including video cropping, rotation, resizing, and sharing through most social media platforms. The test results showed that the VSTM was able to maintain the integrity of the video files, had resistance to visible detection, and was effectively used for small-scale confidential communications. This model offers a practical and secure solution in the field of digital steganography, and has the potential to be applied to a wide range of data protection needs in sensitive digital environments. However, metadata stripping by certain platforms, such as Instagram, affects the message retrieval. The method proves effective and reliable in securing digital information within the video files while preserving quality and ensuring the message integrity.