Coverless Text Information Hiding Techniques: A Review

Abstract

In the digital era, protecting confidential information from unauthorized access is crucial. Information can be represented through a variety of communicative media, including text, video, audio, and images, with text being the most common. Traditional methods require carriers to disguise secret information, leading to carrier modifications which are challenging to avoid steganalysis. In contrast, coverless information hiding does not modify the carrier and transfers hidden information directly via the stego cover’s built-in attributes. The most crucial positive significance for the development of coverless information hiding technology is based on the Chinese mathematical phrase. The primary goal of this review is to examine the most recent findings in the fields of coverless hiding, development approaches, selected datasets, metrics of performance, and issues of hiding applications in English, Chinese, and other languages. The findings demonstrate that researchers have considered the Keywords+ tags, approaches while the approach-based Markov model is mainly used with the English language. Additionally, the study reveals that hiding capacity, success rate, and security analysis metrics are the most common metrics used to evaluate coverless information hiding performance. As a final point, the unresolved issues and potential future directions are addressed to improve hiding capacity and algorithm efficiency, embed and extract information correctly, and extend these techniques to other languages.