Dear Colleagues,

Covert communication is a way of transmitting data without arousing suspicions. Watermarking and steganography are the two widely accepted conventional ways of covert communication. These data-hiding techniques utilize various multimedia objects for confidential communication. Literature has produced several data-hiding techniques to achieve the objective of secure transmission, increased perceptual transparency, and high capacity. However, the recent development in convolution neural networks and auto-encoder-decoder-based data hiding has gained wide attention as compared to handcrafted covert communication techniques. These artificially intelligent models can accurately identify the region of interest for concealing the secret bits. Recently, researchers have started focusing more on convolution neural networks and encoder-decoder-based techniques to achieve better capacity and robustness. This area of research needs to be explored more; therefore, the objective of high imperceptibility, larger capacity, and robust model is no more an issue in data hiding.

This special issue aims to bring together the researchers of data hiding, multimedia security, deep learning-based data hiding, multimedia forensic analysis, and the practitioners of related research fields. The special issue covers the following potential research areas of image forensics:

Ø  Deep learning in steganography

Ø  Deep learning in steganalysis

Ø  Deep learning in watermarking

Ø  Deep learning in watermark analysis

Ø  Fuzzy inference rule-based data hiding

Ø  Video, image, and audio steganography and steganalysis

Ø  Machine learning-based data hiding

Ø  Encryption and decryption-based communication

Ø  Copyright protection

Ø  Coverless data hiding

Ø  Tamper detection and localization

Ø  Self-recovery based watermarking

Ø  Multimedia security over cloud and edges

We look forward to receiving your contributions.

Dr. Aditya Kumar Sahu (Lead guest editor)

Dr. Serdar Solak

Covert Communication; Multimedia Security; Deep Learning; Fuzzy Inference Rule; Tamper Detection and Localization