Steganographic Performance

Steganographic performance research focuses on improving the efficiency and security of hiding information within various media, aiming for high embedding capacity, imperceptible alterations, and robustness against detection. Current research emphasizes deep learning models, including generative adversarial networks (GANs), diffusion models, and convolutional neural networks (CNNs), to achieve these goals across diverse data types like images, audio, video, and even within the parameters of machine learning models themselves. This field is crucial for advancing data security and privacy, with implications for copyright protection, covert communication, and mitigating malicious use of hidden data in various digital contexts.