发表机构
Amirkabir University of Technology (Tehran Polytechnic); Iran University of Science and Technology（阿米尔卡比尔理工大学（德黑兰理工大学）; 伊朗科技大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出一种维度无关的脆弱图像水印算法，采用三角内容感知置换提升安全性，对18种攻击的FPR达0%，在多场景应用中实现高准确率与低时间开销。
AI 中文摘要
随着数字文档交换的增长，保护图像免受矢量量化（VQ）、拼贴等攻击的完整性变得至关重要。现有方法易受这些攻击影响，且局限于固定图像维度。本文提出一种新型维度无关脆弱水印算法，通过用三角内容感知置换（TCA）替代传统哈希函数，提升安全性与篡改定位能力。图像与基于密钥的全局噪声结合后被划分为块，核心创新在于在位平面级应用具有固有雪崩效应的内容依赖置换（TCA），生成唯一的内容依赖水印。对于彩色图像，采用垂直三明治变换融合通道，保留通道间依赖关系，仅带来1.62倍的时间开销；“余数合并”策略消除了填充约束。在50幅灰度图像和10幅彩色图像上针对18种攻击的实验显示，17种攻击的误报率（FPR）为0%、漏报率（FNR）为0%；椒盐噪声导致的FNR可忽略，灰度图像为0.27%，彩色图像为0.14%。平均峰值信噪比（PSNR）：8位图像为51.14 dB，12位图像为75.25 dB，16位图像为99.33 dB；嵌入和提取时间分别为1.61秒和1.63秒。该算法对拼贴、VQ、复制-移动、JPEG（质量5-95）及几何攻击的准确率达100%，为数字取证、医学成像及法律文档认证提供了安全解决方案。
英文摘要
With the growth of digital document exchange, protecting image integrity against attacks such as Vector Quantization (VQ) and collage has become critical. Existing methods are vulnerable to these attacks and limited to fixed image dimensions. This paper presents a novel, dimension-agnostic, fragile watermarking algorithm that enhances security and tamper localization by replacing conventional hash functions with Triangular Content-Aware Permutation (TCA). The image is combined with key-based global noise and divided into blocks. The core innovation is applying content-dependent permutation with intrinsic avalanche effect (TCA) at the bit-plane level, generating a unique content-dependent watermark. For color images, a vertical sandwich transformation merges channels, preserving inter-channel dependency with only 1.62x time increase. The "remainder merging" strategy eliminates padding constraints. Experiments on 50 grayscale and 10 color images under 18 attacks show FPR=0% and FNR=0% for 17 attacks. Salt-and-pepper noise yields negligible FNR of 0.27% (grayscale) and 0.14% (color). Average PSNR is 51.14 dB (8-bit), 75.25 dB (12-bit), and 99.33 dB (16-bit). Embedding and extraction times are 1.61 s and 1.63 s, respectively. The algorithm achieves 100% accuracy against collage, VQ, copy-move, JPEG (quality 5-95), and geometric attacks, providing a secure solution for digital forensics, medical imaging, and legal document authentication.
Comments19 pages, 4 figures, 8 tables
