Demystifying Privacy Preserving Computing

When it comes to privacy, encrypted data-in-transit (eg: HTTPS) or encrypted data-at-rest (eg: encrypted hard-disks) schemes provide sufficient cryptographic guarantees in the battle to protect it. The unresolved problem is encrypting data-in-use. Currently, in order to process data, we need to decrypt, process, and re-encrypt. Computation over unencrypted data may compromise the confidentiality of data and suffer various security attacks
Privacy-Preserving Computing (PPC) has emerged in recent years to enable the secure computation of the data without revealing the content of the data. These techniques look at how to represent data in a form that can be shared, analyzed, and operated on without exposing the raw information
We will discuss current state-of-the-art PPC techniques and the distinct threat models and business use cases they address. The techniques we will cover are: Secure multiparty computation (SMPC), Fully homomorphic encryption (FHE), Differential privacy (DP)


Session info:

Speaker: Tejas Chopra

Senior Software Engineer, Netflix at Netflix, Inc.

Date: 15 maart 2024

Time: 14:10 - 14:55

Relevant tags:
Privacy Security

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