Enhanced video steganography using genetic algorithms, scrambling techniques, and RSA encryption for secure data embedding - younis, Ruaa Nadhim; Mohasefi, Jamshid Bagherzadeh (Edelweiss Applied Science and Technology, 2024)
This study presents a novel approach for secure data embedding into video frames using a combination of RSA encryption, wavelet transforms, and genetic algorithm-based scrambling techniques. The primary focus of the work is to embed image data securely into video frames while preserving the quality of both the video and the extracted image. The method begins by encrypting critical data parameters (such as frame dimensions, block sizes, and other metadata) using the RSA encryption algorithm. These encrypted parameters are then embedded into the last row of the first frame for secure retrieval. The image data is first divided into blocks, processed using a two-level discrete wavelet transform (DWT), and embedded into the high-frequency sub-bands of the video frames. A genetic algorithm-based scrambling technique is used to increase the security and robustness of the embedding process by scrambling the coefficients before embedding. The embedded data is then spread across multiple video frames, ensuring efficient utilization of frame capacity and maintaining imperceptibility. During extraction, the embedded data is retrieved from the video frames, unscrambled using the best key, and decrypted using RSA to reconstruct the original parameters and image. The performance of the proposed method was evaluated using the Signal-to-Noise Ratio (SNR) metric. The SNR for video frames ranged from 36.7 dB to 39.9 dB, indicating minimal distortion. Furthermore, the reconstructed image achieved an SNR of 31.1 dB, showcasing the method's capability to maintain image quality after the embedding and extraction processes. This method demonstrates a secure and efficient approach for video steganography and data hiding, with potential applications in secure communication, copyright protection, and digital watermarking.