A feasibility analysis of secure multiparty computation deployments
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Perustieteiden korkeakoulu |
Master's thesis
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T-110
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en
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59 s.
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Abstract
Imagine a scenario where multiple companies hold valuable information and they want to combine their data for analysis that would benefit them all. In an honest world, the companies could do just that - combine their data. However, in the real world, they might not be able to share their data because of data privacy issues. A cryptographic solution to this problem would be to use secure multiparty computation (SMC). SMC is a useful tool for computing the result of an operation with the inputs of multiple parties, without revealing what the inputs were. As a result, we can perform computations on the data without disclosing it. General multiparty computation is communication heavy and therefore its performance is network bound. One goal of this work is to create a mathematical model for predicting the performance of SMC protocols depending on the network parameters. The model is based on a set of experiments performed on the SHAREMIND SMC framework in our specialized cluster system. We perform analysis of the constructed model and estimate the model parameters. To validate the model, we compare the predictions of the model with the actual algorithm execution time results on the cluster system. To see how the model performs on an alternative system, we deploy a SHAREMIND nodes in the cloud environment and perform the validation there. In the last part of the work, we assess the feasibility of SMC in the cloud environment. The analysis is based on a sample secure survey scenario.Description
Supervisor
Aura, TuomasLaur, Sven