International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

A Deep Dive into Deep Learning-Powered Steganography for Enhanced Security: Review

Abstract

Steganography—the practice of hiding data in digital media—has attracted a lot of interest because of its possible uses in secure communication. This study offers a thorough summary of the most recent developments in steganography, emphasizing the incorporation of deep learning (DL) methods in particular. The review explores several steganographic techniques, classifies them, and assesses the advantages and disadvantages of each. Moreover, it reviews current research projects that use DL to improve security and resilience in steganographic systems. This evaluation finds new trends, problems, and possibilities in the field by examining related studies. The major goal is to advance this field and broaden our understanding of steganography-based secure communication.

Country : Iraq

1 Anfal Shihab Ahmed2 Melad Jader Saeed

  1. Computer Science Department, University of Mosul, Mosul-Iraq
  2. Computer Science Department, University of Mosul, Mosul-Iraq

IRJIET, Volume 8, Issue 3, March 2024 pp. 79-89

doi.org/10.47001/IRJIET/2024.803011

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