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Security and Privacy in Communication Networks. 17th EAI International Conference, SecureComm 2021, Virtual Event, September 6–9, 2021, Proceedings, Part II

Research Article

Quantitative and Qualitative Investigations into Trusted Execution Environments

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  • @INPROCEEDINGS{10.1007/978-3-030-90022-9_19,
        author={Ryan Karl},
        title={Quantitative and Qualitative Investigations into Trusted Execution Environments},
        proceedings={Security and Privacy in Communication Networks. 17th EAI International Conference, SecureComm 2021, Virtual Event, September 6--9, 2021, Proceedings, Part II},
        proceedings_a={SECURECOMM PART 2},
        year={2021},
        month={11},
        keywords={Trusted Execution Environment Hybrid secure computation Performance optimization and modeling},
        doi={10.1007/978-3-030-90022-9_19}
    }
    
  • Ryan Karl
    Year: 2021
    Quantitative and Qualitative Investigations into Trusted Execution Environments
    SECURECOMM PART 2
    Springer
    DOI: 10.1007/978-3-030-90022-9_19
Ryan Karl1,*
  • 1: University of Notre Dame, Notre Dame
*Contact email: rkarl@nd.edu

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.

Keywords
Trusted Execution Environment Hybrid secure computation Performance optimization and modeling
Published
2021-11-04
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-90022-9_19
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