AIForge-Doc: 一个用于检测金融和表单文档中AI伪造篡改的基准测试
AIForge-Doc: A Benchmark for Detecting AI-Forged Tampering in Financial and Form Documents
AI总结：
AIForge-Doc通过生成AI伪造的金融和表单文档数据，揭示了现有检测器对AI伪造篡改的识别能力不足，强调了文档取证领域的新挑战。
摘要：
我们提出了AIForge-Doc，这是首个专门针对基于扩散模型的修复技术在金融和表单文档中进行像素级标注的基准测试。现有的文档伪造数据集依赖于传统数字编辑工具（例如Adobe Photoshop、GIMP），造成关键缺口：最先进的检测器对迅速增长的AI伪造文档欺诈威胁是盲目的。AIForge-Doc通过系统性地在真实世界收据和表单图像中伪造数字字段，使用两个AI修复API--Gemini 2.5 Flash Image和Ideogram v2 Edit，从四个公开文档数据集（CORD、WildReceipt、SROIE、XFUND）中生成4,061张伪造图像，涵盖九种语言，标注有精确到像素的篡改区域掩码，采用DocTamper兼容格式。我们基准测试了三种代表性检测器--TruFor、DocTamper和一个零样本GPT-4o判断者，并发现所有现有方法均显著下降：TruFor在零样本、非分布情况下达到AUC=0.751，与NIST16的AUC=0.96相比；DocTamper在分布情况下达到AUC=0.563，与AUC=0.98相比，像素级IoU=0.020；GPT-4o仅达到0.509--基本上处于偶然水平，证实了AI伪造的值对自动化检测器和VLMs是无法区分的。这些结果表明，AIForge-Doc代表了文档取证领域的一种质的新挑战。
英文摘要：
We present AIForge-Doc, the first dedicated benchmark targeting exclusively diffusion-model-based inpainting in financial and form documents with pixel-level annotation. Existing document forgery datasets rely on traditional digital editing tools (e.g., Adobe Photoshop, GIMP), creating a critical gap: state-of-the-art detectors are blind to the rapidly growing threat of AI-forged document fraud. AIForge-Doc addresses this gap by systematically forging numeric fields in real-world receipt and form images using two AI inpainting APIs -- Gemini 2.5 Flash Image and Ideogram v2 Edit -- yielding 4,061 forged images from four public document datasets (CORD, WildReceipt, SROIE, XFUND) across nine languages, annotated with pixel-precise tampered-region masks in DocTamper-compatible format. We benchmark three representative detectors -- TruFor, DocTamper, and a zero-shot GPT-4o judge -- and find that all existing methods degrade substantially: TruFor achieves AUC=0.751 (zero-shot, out-of-distribution) vs. AUC=0.96 on NIST16; DocTamper achieves AUC=0.563 vs. AUC=0.98 in-distribution, with pixel-level IoU=0.020; GPT-4o achieves only 0.509 -- essentially at chance -- confirming that AI-forged values are indistinguishable to automated detectors and VLMs. These results demonstrate that AIForge-Doc represents a qualitatively new and unsolved challenge for document forensics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
