How to Control User Private Data Access in Mixed Reality Platforms Using Blockchain?

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

48 Downloads (Pure)

Abstract

Mixed reality (MR) has recently emerged as a popular technology enabling people to interact with virtual and physical worlds. MR involves a combination of complex and advanced technologies, including hardware and software, where users’ private data are collected, stored, and processed. Keeping user data secure and private while letting users control their data is not popular among current MR platform owners or third parties. This research proposes a generic blockchain-based MR framework to protect users’ private data and alert them about their data access. Blockchain is a data protection layer on MR platforms and relies on fog to support latency-sensitive MR applications. This article presents a framework with core components, followed by a case study elaborating on accessing medical records to present its usefulness. We also present the results of network performance tests, design considerations, and existing technical challenges.
OriginalsprogEngelsk
TitelProceedings of the 57th Hawaii International Conference on System Sciences
RedaktørerTung Bui
Antal sider10
UdgivelsesstedHonolulu
ForlagHawaii International Conference on System Sciences (HICSS)
Publikationsdato2024
Sider3749-3758
ISBN (Trykt)9780998133171
StatusUdgivet - 2024
BegivenhedThe 57th Hawaii International Conference on System Sciences. HICSS 2024 - Hilton Hawaiian Village Waikiki Beach Resort, Honolulu, USA
Varighed: 3 jan. 20246 jan. 2024
Konferencens nummer: 57
https://hicss.hawaii.edu/

Konference

KonferenceThe 57th Hawaii International Conference on System Sciences. HICSS 2024
Nummer57
LokationHilton Hawaiian Village Waikiki Beach Resort
Land/OmrådeUSA
ByHonolulu
Periode03/01/202406/01/2024
Internetadresse
NavnProceedings of the Annual Hawaii International Conference on System Sciences
ISSN1060-3425

Emneord

  • Blockchain
  • Cloud
  • Data
  • Fog
  • Health
  • Privacy
  • Mixed reality

Citationsformater