Privacy-Preserving Localization using Enclaves

Arslan Khan, Joseph I. Choi, Dave Jing Tian, Tyler Ward, Kevin R.B. Butler, Patrick Traynor, John M. Shea, Tan F. Wong

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

Abstract

Localization is one form of cooperative spectrum sensing that lets multiple sensors work together to estimate the location of a target transmitter. However, the requisite exchange of spectrum measurements leads to exposure of the physical location of participating sensors. Furthermore, in some cases, a compromised participant can reveal the sensitive characteristics of all participants. Accordingly, a lack of sufficient guarantees about data handling discourages such devices from working together. In this paper, we provide the missing data protections by processing spectrum measurements within attestable containers or enclaves. Enclaves provide runtime memory integrity and confidentiality using hardware extensions and have been used to secure various applications [1]-[8]. We use these enclave features as building blocks for new privacy-preserving particle filter protocols that minimize disruption of the spectrum sensing ecosystem. We then instantiate this enclave using ARM TrustZone and Intel SGX, and we show that enclave-based particle filter protocols incur minimal overhead (adding 16 milliseconds of processing to the measurement processing function when using SGX versus unprotected computation) and can be deployed on resource-constrained platforms that support TrustZone (incurring only a 1.01x increase in processing time when doubling particle count from 10,000 to 20,000), whereas cryptographically-based approaches suffer from multiple orders of magnitude higher costs. We effectively deploy enclaves in a distributed environment, dramatically improving current data handling techniques. To our best knowledge, this is the first work to demonstrate privacy-preserving localization in a multi-party environment with reasonable overhead.

Original languageEnglish (US)
Title of host publication2021 IEEE 12th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021
EditorsRajashree Paul
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages269-278
Number of pages10
ISBN (Electronic)9781665406901
DOIs
StatePublished - 2021
Event12th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021 - New York, United States
Duration: Dec 1 2021Dec 4 2021

Publication series

Name2021 IEEE 12th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021

Conference

Conference12th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2021
Country/TerritoryUnited States
CityNew York
Period12/1/2112/4/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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