Vronicle

Abstract

Demonstrating 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.In this paper, we present Vronicle, a method for generating provenance information for videos captured by mobile devices and using that information to verify authenticity of videos. A key feature of Vronicle is the use of Trusted Execution Environments (TEEs) for video capture and post-processing. This aids in constructing fine-grained provenance information that allows the consumer to verify various aspects of the video, thereby defeating numerous fake-video creation methods. Another important feature is the use of fixed-function post-processing units that facilitate verification of provenance information. These units can be deployed in any TEE, either in the mobile device that captures the video or in powerful servers.We present a prototype of Vronicle, which uses ARM TrustZone and Intel SGX for on-device and server-side post-processing, respectively. Moreover, we introduce two methods (and prototype the latter) for secure video capture on mobile devices: one using ARM TrustZone, and another using Google SafetyNet, providing a trade-off between security and immediate deployment. Our evaluation demonstrates that: (1) Vronicle's performance is well-suited for non-real-time use-cases, and (2) offloading post-processing significantly improves Vronicle's performance, matching that of uploading videos to YouTube.