Schedule ACCU 2023 Conference

How to jointly compute on private data, without revealing the inputs, but still getting the outputs

Sometimes multiple parties need to execute a computation where each of the parties holds one of the inputs that they can't or don't want to share with the other parties. A non-technical solution would be to find an external party trusted by all the data holders and have that external party run the computation and announce the results.

But sometimes such a mutually trusted party does not exist. Then a technical solution is to run the computation jointly in such a way that everyone involved learns the result, but nobody learns the inputs of the other parties. In this session we look at some of the protocols and techniques invented for this purpose. Perhaps unexpectedly for these results, high-school level algebra is sufficient for majority of the presentation.

Info

Day: 2023-04-21
Start time: 11:00
Duration: 01:30
Room: Empire
Track: Learning

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