METHODS FOR RELIABLE USER AUTHENTICATION IN VIRTUAL REALITY NETWORKS

Abstract

This article analyzes user authentication methods in virtual reality (VR) networks, focusing on their security characteristics and privacy limitations. Password-based, multifactor, device-based, and behavioral biometric authentication methods are compared. The use of head movements, hand gestures, gaze direction, and voice data processed by VR devices expands authentication capabilities but also introduces privacy-related risks. Based on a review of the scientific literature, an adaptive conceptual model is proposed that combines initial session verification, continuous risk assessment during the session, and additional authentication when necessary.