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Encrypted Computation: What if Decryption Wasn’t Needed?

Katharine Jarmul | GOTO Copenhagen 2024

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If you are curious about the field of cryptography and what it has to offer data science and machine learning, this talk is for you! We'll dive into the field of encrypted computation, where decryption isn't needed in order to perform calculations, transformations and operations on the data. You'll learn some of the core mathematical theory behind why and how this works, as well as the differences between approaches like homomorphic encryption and secure multi-party computation. At the end, you'll get some pointers and open-source library hints on where to go next and how to start using encrypted computation for problems you are solving the hard way (or not solving at all).

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Transcript

If you are curious about the field of cryptography and what it has to offer data science and machine learning, this talk is for you!

We'll dive into the field of encrypted computation, where decryption isn't needed in order to perform calculations, transformations and operations on the data. You'll learn some of the core mathematical theory behind why and how this works, as well as the differences between approaches like homomorphic encryption and secure multi-party computation. At the end, you'll get some pointers and open-source library hints on where to go next and how to start using encrypted computation for problems you are solving the hard way (or not solving at all).

About the speakers

Katharine Jarmul

Katharine Jarmul

Principal Data Scientist at Thoughtworks & O'Reilly Author