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Transitioning from testbeds to ships: an experience study in deploying the TIPPERS Internet of Things platform to the US Navy

  • Dave Archer
  • , Michael A. August
  • , Georgios Bouloukakis
  • , Christopher Davison
  • , Mamadou H. Diallo
  • , Dhrubajyoti Ghosh
  • , Christopher T. Graves
  • , Michael Hay
  • , Xi He
  • , Peeter Laud
  • , Steve Lu
  • , Ashwin Machanavajjhala
  • , Sharad Mehrotra
  • , Gerome Miklau
  • , Alisa Pankova
  • , Shantanu Sharma
  • , Nalini Venkatasubramanian
  • , Guoxi Wang
  • , Roberto Yus
  • Galois Inc.
  • Naval Information Warfare Center
  • Long Beach VA and University of California
  • Ball State University
  • Colgate University
  • University of Waterloo
  • Cybernetica AS
  • Inc.
  • Duke University
  • UMass Amherst

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

This paper describes the collaborative effort between privacy and security researchers at nine different institutions along with researchers at the Naval Information Warfare Center to deploy, test, and demonstrate privacy-preserving technologies in creating sensor-based awareness using the Internet of Things (IoT) aboard naval vessels in the context of the US Navy’s Trident Warrior 2019 exercise. Funded by DARPA through the Brandeis program, the team built an integrated IoT data management middleware, entitled TIPPERS, that supports privacy by design and integrates a variety of Privacy Enhancing Technologies (PETs), including differential privacy, computation on encrypted data, and fine-grained policies. We describe the architecture of TIPPERS and its use in creating a smart ship that offers IoT-enabled services such as occupancy analysis, fall detection, detection of unauthorized access to spaces, and other situational awareness scenarios. We describe the privacy implications of creating IoT spaces that collect data that might include individuals’ data (e.g., location) and analyze the tradeoff between privacy and utility of the supported PETs in this context.

langue originaleAnglais
Pages (de - à)501-517
Nombre de pages17
journalJournal of Defense Modeling and Simulation
Volume19
Numéro de publication3
Les DOIs
étatPublié - 1 juil. 2022
Modification externeOui

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