PRIVACY AND DATA PROTECTION IN METAUNIVERSITY: SECURING VR CLASSROOMS AND IN-WORLD CHAT

Abstract

This article examines privacy and data protection in metauniversity that integrates VR classrooms, internal text/voice chat, and the synchronization of learning outcomes with university information systems. It demonstrates that the security of such platforms is determined by a combination of threats: account and avatar compromise, XR telemetry and biosignal leaks, integration and network synchronization risks, and sociotechnical communications abuse. The goal of the study is to develop a reproducible data and communications security architecture that ensures the confidentiality and integrity of information in real time. The methodology includes data classification, threat modeling, and the formalization of access policies within the privacy-by-design paradigm. The proposed architecture includes SSO/MFA/RBAC, chat and VR session moderation, secure integration with external information systems, cryptographic protection (TLS, AES-GCM, KMS/HSM), and a logging/forensics circuit (SIEM, immutable audit logs).