Research progress of color image steganalysis

XU Meng; LUO Xiangyang; WANG Jinwei; WANG Hao

doi:10.11959/j

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Research progress of color image steganalysis

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- Research progress of color image steganalysis
- Chinese Journal of Network and Information Security Vol. 10, Issue 4, Pages: 49-62(2024)
- 作者机构：
  
  1.数学工程与先进计算国家重点实验室,河南郑州 450001
  2.南京信息工程大学计算机与软件学院,江苏南京 210044
  3.南京理工大学自动化学院,江苏南京 210014
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(U1804263;U1736214;62172435)
- DOI：10.11959/j
  CLC： TP309.7
- Received：22 January 2024，
  
  Revised：2024-07-28，
  
  Published：25 August 2024
- 稿件说明：
移动端阅览
徐萌, 罗向阳, 王金伟, 等. 彩色图像隐写分析研究进展[J]. 网络与信息安全学报, 2024, 10(4): 49-62.

Format: XU M, LUO X G, WANG J W, et al. Research progress of color image steganalysis[J]. Chinese Journal of Network and Information Security, 2024, 10(4): 49-62.
徐萌, 罗向阳, 王金伟, 等. 彩色图像隐写分析研究进展[J]. 网络与信息安全学报, 2024, 10(4): 49-62. DOI： 10.11959/j.

Format: XU M, LUO X G, WANG J W, et al. Research progress of color image steganalysis[J]. Chinese Journal of Network and Information Security, 2024, 10(4): 49-62. DOI： 10.11959/j.

摘要

传统的加密通信技术易被察觉，很难满足安全通信的需求。数字隐写术通过对载体修改来隐藏信息，可以实现隐蔽通信。但是，隐写术也可能被用于非法行为，使检测隐写术的隐写分析技术受到了越来越多的关注，因此隐写分析技术具有重大的研究意义。深度学习在计算机视觉、模式识别和自然语言处理等领域取得了很多研究成果，给隐写分析带来了新机遇，提出了新挑战，促使隐写分析产生新思想、新方法。彩色图像是互联网传输过程中的主流载体。但现有的彩色图像隐写分析特征主要依赖于人工设计，且隐写分析特征将彩色图像当成3个独立的灰度图像，并未充分考虑彩色图像三通道间的内部联系，对载密图像的检测能力有待提高。深度学习在彩色图像隐写分析领域中的应用也处于初步阶段。因此在介绍隐写和隐写分析的概念、分类和研究意义，概述其研究现状后，重点介绍了几种针对彩色图像的隐写分析关键技术，对其进行对比和总结，并分析其发展趋势。

Abstract

Traditional encrypted communication technologies have been easily detected and have struggled to meet the needs of secure communication. Steganography

capable of hiding information by modifying the carrier

has been utilized to realize covert communication. However

the potential for steganography to be employed in illegal acts has directed increasing attention towards steganalysis for the detection of steganography

thereby bestowing great research significance upon it. Deep learning has yielded numerous research achievements in fields such as computer vision

pattern recognition

and natural language processing

introducing new opportunities and challenges to steganalysis. These advancements have propelled the generation of new ideas and methods in steganalysis. Currently

color images constitute the mainstream carrier in the process of internet transmission. Nevertheless

existing steganalysis features for color images primarily rely on manual design and often treat the color image as three independent grayscale images

without fully considering the internal relationships between the three color channels

thus necessitating an improvement in detection capabilities for encrypted images. The application of deep learning in the field of color image steganalysis remains in its preliminary stage. The concepts

classifications

and research significance of steganography and steganalysis were introduced

along with an outline of their current research status. Several key techniques for the steganalysis of color images were introduced

compared

summarized

and their development trends were analyzed.

关键词

Keywords

references

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