Аннотация:
With the growing use of the internet and social media, data security has become a major
issue. Thus, researchers are focusing on data security techniques such as steganography and steganalysis.
Steganography is the approach of concealing the existence of secret messages in digital media for secure
transmission. Steganalysis techniques aim to detect the existence of concealed messages and extract them.
Digital image steganography and steganalysis techniques are classified into the spatial and transform
domains. In this paper, we provide a detailed survey of the state-of-the-art works that have been performed
in two-dimensional and three-dimensional image steganalysis. We present the most popular datasets and
explain some steganographic methods for embedding hidden data. Steganalysis is a very difficult task due
to the lack of information about the characteristics of the cover media that can be exploited to detect hidden
messages. Therefore, we review studies performed on image steganalysis in the spatial and transform
domains using classical machine learning and deep learning approaches. Additionally, we present open
challenges and discuss some directions for future research.
