Privacy-preserving Pseudonym Schemes for Personalized 3D Avatars in Mobile Social Metaverses

TL;DR

This paper proposes a privacy-preserving framework for personalized 3D avatars in mobile social metaverses, using avatar pseudonyms and a game-theoretic approach to protect user identity while maintaining immersion.

Contribution

It introduces a novel pseudonym-based avatar construction framework and a metric for privacy evaluation, employing deep reinforcement learning for resource optimization.

Findings

The framework effectively protects avatar privacy in simulations.

The pseudonym strategy reduces identity leakage risks.

Simulation results demonstrate the approach's feasibility and efficiency.

Abstract

The emergence of mobile social metaverses, a novel paradigm bridging physical and virtual realms, has led to the widespread adoption of avatars as digital representations for Social Metaverse Users (SMUs) within virtual spaces. Equipped with immersive devices, SMUs leverage Edge Servers (ESs) to deploy their avatars and engage with other SMUs in virtual spaces. To enhance immersion, SMUs incline to opt for 3D avatars for social interactions. However, existing 3D avatars are typically generated through scanning the real faces of SMUs, which can raise concerns regarding information privacy and security, such as profile identity leakages. To tackle this, we introduce a new framework for personalized 3D avatar construction, leveraging a two-layer network model that provides SMUs with the option to customize their personal avatars for privacy preservation. Specifically, our approach introduces avatar pseudonyms to jointly safeguard the profile and digital identity privacy of the generated avatars. Then, we design a novel metric named Privacy of Personalized Avatars (PoPA), to evaluate effectiveness of the avatar pseudonyms. To optimize pseudonym resource, we model the pseudonym distribution process as a Stackelberg game and employ Deep Reinforcement Learning (DRL) to learn equilibrium strategies under incomplete information. Simulation results validate the efficacy and feasibility of our proposed schemes for mobile social metaverses.