VVSec: Securing Volumetric Video Streaming via Benign Use of Adversarial Perturbation

Zhongze Tang, Xianglong Feng, Yi Xie, Huy Phan, Tian Guo, Bo Yuan, Sheng Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Volumetric video (VV) streaming has drawn an increasing amount of interests recently with the rapid advancements in consumer VR/AR devices and the relevant multimedia and graphics research. While the resource and performance challenges in volumetric video streaming have been actively investigated by the multimedia community, the potential security and privacy concerns with this new type of multimedia have not been studied. We for the first time identify an effective threat model that extracts 3D face models from volumetric videos and compromises face ID-based authentications To defend against such attack, we develop a novel volumetric video security mechanism, namely VVSec, which makes benign use of adversarial perturbations to obfuscate the security and privacy-sensitive 3D face models. Such obfuscation ensures that the 3D models cannot be exploited to bypass deep learning-based face authentications. Meanwhile, the injected perturbations are not perceivable by the end-users, maintaining the original quality of experience in volumetric video streaming. We evaluate VVSec using two datasets, including a set of frames extracted from an empirical volumetric video and a public RGB-D face image dataset. Our evaluation results demonstrate the effectiveness of both the proposed attack and defense mechanisms in volumetric video streaming.

Original languageEnglish (US)
Title of host publicationMM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages3614-3623
Number of pages10
ISBN (Electronic)9781450379885
DOIs
StatePublished - Oct 12 2020
Event28th ACM International Conference on Multimedia, MM 2020 - Virtual, Online, United States
Duration: Oct 12 2020Oct 16 2020

Publication series

NameMM 2020 - Proceedings of the 28th ACM International Conference on Multimedia

Conference

Conference28th ACM International Conference on Multimedia, MM 2020
Country/TerritoryUnited States
CityVirtual, Online
Period10/12/2010/16/20

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

Keywords

  • adversarial perturbation
  • face authentication
  • video streaming
  • volumetric video

Fingerprint

Dive into the research topics of 'VVSec: Securing Volumetric Video Streaming via Benign Use of Adversarial Perturbation'. Together they form a unique fingerprint.

Cite this