OVRseen: Auditing Network Traffic and Privacy Policies in Oculus VR

TL;DR

This paper presents OVRseen, a novel system for analyzing network traffic and privacy policies in Oculus VR, revealing significant undisclosed data flows and privacy risks in VR applications.

Contribution

The paper introduces OVRseen, the first comprehensive methodology for analyzing network traffic and privacy policies in Oculus VR, including decryption of traffic and comparison with policy disclosures.

Findings

70% of data flows were not properly disclosed in privacy policies

VR apps expose PII, device info, and VR-specific data types

69% of data flows are used for unrelated purposes

Abstract

Virtual reality (VR) is an emerging technology that enables new applications but also introduces privacy risks. In this paper, we focus on Oculus VR (OVR), the leading platform in the VR space and we provide the first comprehensive analysis of personal data exposed by OVR apps and the platform itself, from a combined networking and privacy policy perspective. We experimented with the Quest 2 headset and tested the most popular VR apps available on the official Oculus and the SideQuest app stores. We developed OVRseen, a methodology and system for collecting, analyzing, and comparing network traffic and privacy policies on OVR. On the networking side, we captured and decrypted network traffic of VR apps, which was previously not possible on OVR, and we extracted data flows, defined as <app, data type, destination>. Compared to the mobile and other app ecosystems, we found OVR to be more centralized and driven by tracking and analytics, rather than by third-party advertising. We show that the data types exposed by VR apps include personally identifiable information (PII), device information that can be used for fingerprinting, and VR-specific data types. By comparing the data flows found in the network traffic with statements made in the apps' privacy policies, we found that approximately 70% of OVR data flows were not properly disclosed. Furthermore, we extracted additional context from the privacy policies, and we observed that 69% of the data flows were used for purposes unrelated to the core functionality of apps.