“Video Steganography Using 3D Convolutional Neural Networks,” in Mediterranean Conference on Pattern Recognition and Artificial Intelligence, pp. M Abdolmohammadi, RM Toroghi, and A Bastanfard (2019). This survey is intended to provide a complete guide for common people and new researchers and scholars approaching this field, sight on the existing and the future of steganography and steganalysis.Īach T, Kaup A, Mester R (1993) Statistical model-based change detection in moving video. Additionally, experiments were done using image steganography techniques to analyse the recent trends. It is a corpus of the author’s opinion and the viewpoints of different other researchers and practitioners, working in this discipline. Further, the paper also takes stock the dataset and tools available for multimedia steganography and steganalysis with the examples where steganography has been used in real-life.

The state-of-the-art techniques for steganography and steganalysis (image and video) have been deliberated for the last 5 years literature. Also, what has been accomplished in order to critically examine what has been done well and what ought to be done better. This article scrutinizes where the discipline of steganography and steganalysis at this point in time in context to the common user and new researchers in terms of current trends.

In any specialism of human endeavour, it is imperative to periodically pause and review the state of the discipline for what has been achieved till date. Steganography and steganalysis is a relatively new-fangled scientific discipline in security systems and digital forensics, respectively, but one that has matured greatly over the past two decades.

Use of steganography in cyber espionage