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Quantitative and Qualitative Investigations into Trusted Execution Environments

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Security and Privacy in Communication Networks (SecureComm 2021)

Abstract

I propose to develop a quantitative and qualitative framework to integrate a Trusted Execution Environment (TEE) into the pipeline of secure computation by combining it with other cryptographic primitives. Such a hybrid framework will utilize mathematical and statistical modeling techniques to decide how to combine TEE and cryptographic primitives and evaluate the potential for performance improvement by moving secure computation processes into or out of a TEE. Ideally, I will be able to determine when to combine TEEs with pure-cryptography techniques to improve performance for a task, instead of simply using either method alone and only achieving suboptimal performance. The final goal is to design and develop an actionable decision-making framework, and utilize it to optimize the secure computation process.

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Author information

Authors and Affiliations

  1. University of Notre Dame, Notre Dame, IN, 46556, USA

    Ryan Karl

Authors
  1. Ryan Karl
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Correspondence to Ryan Karl .

Editor information

Editors and Affiliations

  1. Télécom SudParis, Institut Polytechnique de Paris, Palaiseau, France

    Joaquin Garcia-Alfaro

  2. University of Kent Canterbury, Canterbury, Kent, UK

    Shujun Li

  3. University of Washington, Seattle, WA, USA

    Radha Poovendran

  4. Télécom SudParis, Institut Polytechnique de Paris, Palaiseau, France

    Hervé Debar

  5. Google Inc., New York, NY, USA

    Moti Yung

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Karl, R. (2021). Quantitative and Qualitative Investigations into Trusted Execution Environments. In: Garcia-Alfaro, J., Li, S., Poovendran, R., Debar, H., Yung, M. (eds) Security and Privacy in Communication Networks. SecureComm 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 399. Springer, Cham. https://doi.org/10.1007/978-3-030-90022-9_19

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  • DOI: https://doi.org/10.1007/978-3-030-90022-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90021-2

  • Online ISBN: 978-3-030-90022-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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