Image Steganography: A Review of the Recent Advances

Nandhini Subramanian, Omar Elharrouss, Somaya Al-Maadeed, Ahmed Bouridane

Research output: Contribution to journalArticlepeer-review

128 Citations (Scopus)
139 Downloads (Pure)


Image Steganography is the process of hiding information which can be text, image or video inside a cover image in a way that is not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography to protect and secure the transmitted data, has received increased attention recently. The main goal of this paper is to explore and discuss various deep learning methods available in image steganography field. Deep learning techniques used for image steganography can broadly be divided into three categories - traditional methods, CNN-based and GAN-based methods. Along with the methodology, an elaborate summary on the datasets used, experimental set-ups considered and the evaluation metrics commonly used are described in this paper. A table summarizing all the details are also provided for easy reference. This paper aims to help the fellow researchers by compiling the current trends, challenges and some future direction in this field.

Original languageEnglish
Pages (from-to)23409-23423
Number of pages15
JournalIEEE Access
Early online date25 Jan 2021
Publication statusPublished - 10 Feb 2021


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