Image Steganalysis

Image steganalysis aims to detect hidden information embedded within digital images or videos, a crucial task in digital forensics and security. Current research focuses on developing robust steganalysis methods using deep learning architectures, such as convolutional neural networks, and exploring alternative approaches like those based on invertible neural networks or analyzing inherent properties of video coding like motion vector optimality. These advancements improve detection accuracy and efficiency, impacting areas such as secure communication and copyright protection by enhancing the ability to identify hidden data and malicious manipulations.