Vronicle: A System for Producing Videos with Verifiable Provenance
Yuxin (Myles) Liu, Yoshimichi Nakatsuka, Ardalan Amiri Sani, Sharad, Agarwal, Gene Tsudik

TL;DR
Vronicle is a system that embeds fine-grained, verifiable provenance information into videos using Trusted Execution Environments, enabling authentication of the camera and applied filters to combat video manipulation.
Contribution
It introduces a novel provenance information design and leverages Intel SGX enclaves to enable secure, verifiable video provenance with improved performance over prior methods.
Findings
Supports verification of camera origin and applied filters
Achieves better performance suitable for offline use
Resistant to various video manipulation techniques
Abstract
Demonstrating the veracity of videos is a longstanding problem that has recently become more urgent and acute. It is extremely hard to accurately detect manipulated videos using content analysis, especially in the face of subtle, yet effective, manipulations, such as frame rate changes or skin tone adjustments. One prominent alternative to content analysis is to securely embed provenance information into videos. However, prior approaches have poor performance and/or granularity that is too coarse. To this end, we construct Vronicle -- a video provenance system that offers fine-grained provenance information and substantially better performance. It allows a video consumer to authenticate the camera that originated the video and the exact sequence of video filters that were subsequently applied to it. Vronicle exploits the increasing popularity and availability of Trusted Execution…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Security and Verification in Computing · Adversarial Robustness in Machine Learning
