Open Access

REVIEW

Digital Image Steganographer Identification: A Comprehensive Survey

Qianqian Zhang^1,2,3, Yi Zhang^1,2, Yuanyuan Ma³, Yanmei Liu^1,2, Xiangyang Luo^1,2,*

1 Information Engineering University, Zhengzhou, 450001, China
2 Key Laboratory of Cyberspace Situation Awareness of Henan Province, Zhengzhou, 450001, China
3 College of Computer and Information Engineering, Henan Normal University, Xinxiang, 453007, China

* Corresponding Author: Xiangyang Luo. Email:

Computers, Materials & Continua 2024, 81(1), 105-131. https://doi.org/10.32604/cmc.2024.055735

Received 05 July 2024; Accepted 05 September 2024; Issue published 15 October 2024

Abstract

The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse. Identifying steganographer is essential in tracing secret information origins and preventing illicit covert communication online. Accurately discerning a steganographer from many normal users is challenging due to various factors, such as the complexity in obtaining the steganography algorithm, extracting highly separability features, and modeling the cover data. After extensive exploration, several methods have been proposed for steganographer identification. This paper presents a survey of existing studies. Firstly, we provide a concise introduction to the research background and outline the issue of steganographer identification. Secondly, we present fundamental concepts and techniques that establish a general framework for identifying steganographers. Within this framework, state-of-the-art methods are summarized from five key aspects: data acquisition, feature extraction, feature optimization, identification paradigm, and performance evaluation. Furthermore, theoretical and experimental analyses examine the advantages and limitations of these existing methods. Finally, the survey highlights outstanding issues in image steganographer identification that deserve further research.

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Keywords

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