VisGuard: Securing Visualization Dissemination through Tamper-Resistant Data Retrieval
Huayuan Ye, Juntong Chen, Shenzhuo Zhang, Yipeng Zhang, Changbo Wang, Chenhui Li

TL;DR
VisGuard is a tamper-resistant framework that embeds recoverable metadata links into visualization images, ensuring data integrity and enabling applications like tampering detection and copyright protection.
Contribution
It introduces robust techniques for embedding metadata into images that withstand tampering, enhancing visualization dissemination security and reliability.
Findings
High data retrieval accuracy after tampering
Superior embedding capacity and security
Effective tampering detection and copyright protection
Abstract
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…
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