Image Steganography

Image steganography focuses on concealing secret data within seemingly innocuous cover media, like images or audio, aiming for undetectability and high embedding capacity. Current research emphasizes developing robust and secure methods using deep learning architectures, such as diffusion models, generative adversarial networks (GANs), and convolutional neural networks (CNNs), often incorporating techniques like invertible neural networks and adaptive perturbation optimization to improve imperceptibility and resistance to steganalysis. This field is significant due to its implications for secure communication and data protection, with ongoing efforts to improve the robustness of steganographic methods against increasingly sophisticated detection techniques. The development of more efficient and secure steganography techniques has implications for various applications, including copyright protection and covert communication.