数字图像隐写分析综述  

Review of Steganalysis for Digital Images

作　　者：王子驰 李斌[2] 冯国瑞[1] 张新鹏[1] WANG Zichi;LI Bin;FENG Guorui;ZHANG Xinpeng(School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China;Shenzhen Key Laboratory of Media Security,Shenzhen University,Shenzhen 518060,Guangdong,China)

机构地区：[1]上海大学通信与信息工程学院,上海200444 [2]深圳大学深圳市媒体信息内容安全重点实验室,广东深圳518060

出　　处：《应用科学学报》2024年第5期723-732,共10页Journal of Applied Sciences

基　　金：国家自然科学基金(No.U22B2047,No.62376148,No.62002214);上海市“晨光计划”项目(No.22CGA46);深圳市媒体信息内容安全重点实验室开放基金项目(No.ML-2022-01)资助。

摘　　要：数字隐写是机密信息安全传递的重要方式,将机密信息隐藏于普通多媒体数据(图像或视音频)中可以实现隐蔽传输。而发现机密信息的隐蔽传输可采用隐写分析技术,隐写分析根据隐写引起的载体数据统计异常来判断多媒体数据是否含有秘密信息。近年来,隐写与隐写分析在相互对抗中不断进步与发展。随着社交网络的兴起,数字图像已成为社交媒介之一并广泛传播。本文以数字图像为例,梳理了近十余年数字图像隐写分析研究的发展现状;综述了传统隐写分析与深度学习隐写分析;探讨了各类方法面临的挑战,并展望了隐写分析的发展趋势。Digital steganography plays a crucial role in securely transmitting confidential data by concealing it within common multimedia,such as images,videos,and audio,to facilitate covert communication.To discover the covert communication of steganography,the technique of steganalysis can be employed.Steganalysis determines whether a given multimedia object contains secret data according to the statistical anomaly of stego data caused by steganography.In recent years,both steganography and steganalysis have made significant progress and development in their mutual confrontation,particularly in the context of the growing prevalence of digital images on social networks.Focusing on digital images,this paper sorts out the development of steganalysis in the past decade,and reviews the traditional steganalysis and deep learning based-steganalysis.Then,the limitations of each approach are discussed.Finally,the study offers insights into the prospective development trends in steganalysis.

关 键 词：隐写 隐写分析 数字图像 特征提取 深度学习 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]