NTRF-Net：一种用于检测数字图像中隐藏数据的模糊逻辑增强卷积神经网络

IF 2.7 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing-Image Communication Pub Date : 2025-08-28 DOI:10.1016/j.image.2025.117401

Ntivuguruzwa Jean De La Croix , Tohari Ahmad , Fengling Han , Royyana Muslim Ijtihadie

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引用次数: 0

摘要

隐写分析的最新进展集中在检测图像中的隐藏信息，但是在高级自适应隐写术中定位隐藏数据的可能位置仍然是一个关键的挑战，特别是对于在公共网络上共享的图像。本文介绍了一种新的隐写分析方法NTRF-Net，用于识别数字图像中被隐写改变的像素的位置。NTRF-Net关注图像的空间特征，在卷积神经网络中结合随机特征选择和模糊逻辑，通过修改图生成、特征分类和像素分类三个阶段进行工作。NTRF-Net显示出较高的准确率，准确率和F1分数分别达到98.2%和86.2%。ROC曲线和AUC值突出了所提出的NTRF-Net的强隐写改变识别能力，其优于现有基准。

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NTRF-Net: A fuzzy logic-enhanced convolutional neural network for detecting hidden data in digital images

Recent advancements in steganalysis have focused on detecting hidden information in images, but locating the possible positions of concealed data in advanced adaptive steganography remains a crucial challenge, especially for images shared over public networks. This paper introduces a novel steganalysis approach, NTRF-Net, designed to identify the location of steganographically altered pixels in digital images. NTRF-Net, focusing on spatial features of an image, combines stochastic feature selection and fuzzy logic within a convolutional neural network, working through three stages: modification map generation, feature classification, and pixel classification. NTRF-Net demonstrates high accuracy, achieving 98.2 % and 86.2 % for the accuracy and F₁ Score, respectively. The ROC curves and AUC values highlight the strong steganographically altered recognition capabilities of the proposed NTRF-Net, which outperform existing benchmarks.

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来源期刊

Signal Processing-Image Communication 工程技术-工程：电子与电气

CiteScore

8.40

自引率

2.90%

发文量

138

审稿时长

5.2 months

期刊介绍： Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following: To present a forum for the advancement of theory and practice of image communication. To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems. To contribute to a rapid information exchange between the industrial and academic environments. The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world. Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments. Subjects of interest include image/video coding, 3D video representations and compression, 3D graphics and animation compression, HDTV and 3DTV systems, video adaptation, video over IP, peer-to-peer video networking, interactive visual communication, multi-user video conferencing, wireless video broadcasting and communication, visual surveillance, 2D and 3D image/video quality measures, pre/post processing, video restoration and super-resolution, multi-camera video analysis, motion analysis, content-based image/video indexing and retrieval, face and gesture processing, video synthesis, 2D and 3D image/video acquisition and display technologies, architectures for image/video processing and communication.