Digital Steganography : A Comprehensive Study on Various Methods for Hiding Secret Data in a Cover file

Abstract

This research paper offers an in-depth examination of digital steganography, with a focus on the diverse methodologies utilized for embedding secret data within cover files. Steganography, the practice of concealing information within other non-secret data, ensures the hidden message remains undetectable to unauthorized observers. This study systematically reviews both traditional and modern steganographic techniques, dissecting their fundamental mechanisms, advantages, and weaknesses. Techniques explored include Least Significant Bit (LSB) insertion, discrete cosine transform (DCT), discrete wavelet transform (DWT), and innovative methods leveraging deep learning and adaptive algorithms. Each method is assessed for its imperceptibility, robustness, and data capacity, offering a comparative analysis to underscore their respective practical applications and limitations. Additionally, the paper delves into steganalysis—methods for detecting hidden information—to provide a comprehensive perspective on the field. Through experimental evaluation and theoretical analysis, this study seeks to enhance the understanding of digital steganography, presenting insights that could inform future research and the development of more secure data hiding techniques.