用遗传算法选视频隐写最佳区域，保画质又高效。
Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms
- 用遗传算法自动找视频中适合藏数据的区域。
- 嵌入后峰值信噪比达64–75分贝，几乎看不出改动。
- 加密嵌入速度快，适合实时隐写应用。
随着互联网普及，数据安全与隐私保护需求日益增长，推动了视频隐写技术的研究。该技术将秘密信息隐藏在视频载体中以避免被检测。隐写效果取决于能否在不破坏原视频质量的前提下高效嵌入数据。本文提出一种新方法：利用遗传算法（GA）识别视频载体中的感兴趣区域（ROI），即最适合嵌入数据的区域。秘密数据先经高级加密标准（AES）加密，再嵌入至不超过视频总量10%的区域内，确保数据安全。采用峰值信噪比（PSNR）和编码/解码时间作为评估指标。实验结果表明，该方法具有高嵌入容量与效率，PSNR在64至75 dB之间，说明嵌入后视频几乎无法察觉异常；同时编码与解码速度较快，适用于实时应用场景。
原文摘要 · Abstract (English)
With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI is the area in the video that is the most suitable for data embedding. The secret data is encrypted using the Advanced Encryption Standard (AES), which is a widely accepted encryption standard, before being embedded into the cover video, utilizing up to 10% of the cover video. This process ensures the security and confidentiality of the embedded data. The performance metrics for assessing the proposed method are the Peak Signal to Noise Ratio (PSNR) and the encoding and decoding time. The results show that the proposed method has a high embedding capacity and efficiency, with a PSNR ranging between 64 and 75 dBs, which indicates that the embedded data is almost indistinguishable from the original video. Additionally, the method can encode and decode data quickly, making it efficient for real time applications.
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