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

Author

Listed:
  • 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

Abstract

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.

Suggested Citation

  • 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 Machan, 2022. "Transitioning from testbeds to ships: an experience study in deploying the TIPPERS Internet of Things platform to the US Navy," The Journal of Defense Modeling and Simulation, , vol. 19(3), pages 501-517, July.
    • Handle: RePEc:sae:joudef:v:19:y:2022:i:3:p:501-517
    DOI: 10.1177/1548512920956383
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    References listed on IDEAS

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    1. Fabio Bagalà & Clemens Becker & Angelo Cappello & Lorenzo Chiari & Kamiar Aminian & Jeffrey M Hausdorff & Wiebren Zijlstra & Jochen Klenk, 2012. "Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-9, May.
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