Existing deep learning-based steganography detection methods utilize convolution to
automatically capture and learn steganographic features, yielding higher detection efficiency …

Steganography is often used by hackers or illegal organizations as a vehicle for information
interception of medical images. Exchanged between PACS or communicated during …

To enhance our ability to model long-range semantical dependencies, we introduce a novel
approach for linguistic steganography through English translation. This method leverages …

In scenarios where steganographic texts from various steganographic domains generated
by different generative steganography algorithms are mixed, most existing linguistic …

Currently, video question answering (VideoQA) algorithms relying on video-text pretraining
models employ intricate unimodal encoders and multimodal fusion Transformers, which …

With the evolution of generative linguistic steganography techniques, conventional
steganalysis falls short in robustly quantifying the alterations induced by steganography …

In the research conducted and reported herein, we demonstrate the ability to generate and
manipulate synthetic satellite images by employing a set of deep learning architectures (DL) …

The generative linguistic steganography in social networks have potential huge abuse and
regulatory risks, with serious implications for information security, especially in the era of …

The objective of linguistic steganography is to embed additional data in text carriers for
covert communication, whereas linguistic steganalysis, as a counter technology to linguistic …

Text teganography is a method used to hide confidential messages in a message's text
without arousing suspicion. This technique has been used in the past, from ancient Greece's …