让可视化图像抗篡改，丢失也能找回原始数据。
VisGuard: Securing Visualization Dissemination through Tamper-Resistant Data Retrieval
- 将元数据链接重复嵌入图像，抗裁剪编辑。
- 篡改后仍可准确恢复数据链接，成功率超95%。
- 适合版权保护与交互图表重建场景。
可视化传播主要以位图形式进行，常导致源代码、交互功能和元数据等关键信息丢失。现有方法虽尝试将元数据嵌入图像以实现可视化图像数据检索（VIDR），但多数对在线分发中的常见篡改（如裁剪、编辑）过于脆弱。为此，我们提出VisGuard，一种抗篡改的VIDR框架，可可靠地将元数据链接嵌入可视化图像中，即使图像遭受严重篡改，嵌入链接仍可被恢复。我们提出多种增强鲁棒性的技术，包括重复数据分块、可逆信息广播以及基于锚点的裁剪定位方案。VisGuard支持交互图表重建、篡改检测和版权保护等多种应用。我们在多个数据集上进行了全面实验，验证了其在数据检索准确率、嵌入容量及对篡改和隐写分析的安全性方面的优越性能，证明了其在保障可视化传播与信息传递方面的有效性。
原文摘要 · Abstract (English)
The dissemination of visualizations is primarily in the form of raster images, which often results in the loss of critical information such as source code, interactive features, and metadata. While previous methods have proposed embedding metadata into images to facilitate Visualization Image Data Retrieval (VIDR), most existing methods lack practicability since they are fragile to common image tampering during online distribution such as cropping and editing. To address this issue, we propose VisGuard, a tamper-resistant VIDR framework that reliably embeds metadata link into visualization images. The embedded data link remains recoverable even after substantial tampering upon images. We propose several techniques to enhance robustness, including repetitive data tiling, invertible information broadcasting, and an anchor-based scheme for crop localization. VisGuard enables various applications, including interactive chart reconstruction, tampering detection, and copyright protection. We conduct comprehensive experiments on VisGuard's superior performance in data retrieval accuracy, embedding capacity, and security against tampering and steganalysis, demonstrating VisGuard's competence in facilitating and safeguarding visualization dissemination and information conveyance.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。