Privacy-enhancing technologies (PETs)

PETs are special techniques in computer science that allow the execution of algorithms on protected data with public outcomes, without ever breaking the confidentiality of the data. For example, they can be used to train machine learning algorithms on datasets from different entities such that only the learned model, but not the original datasets, become known. PETs also allow attesting that a public algorithm outputs a certain value based on a secret input, without revealing anything but the output. Based on their guarantee of confidentiality and correctness, they may have numerous applications in computer science and beyond.

In this talk, we will provide a high-level overview of the most relevant aspects of PETs and discuss some core technologies, such as zero-knowledge proofs, private set intersection protocols, and multi-party computation protocols. The talk will provide a general introduction to these topics and discuss existing and possible future applications where the aforementioned technologies play a crucial role.

The talk will be given by Luisa Siniscalchi and Carsten Baum, who will each talk for 45 minutes.

Arranged by: Finn Gustafsson, IDA IT

Free for members of IDA IT and DANSK IT

Refreshments: Coffee / tea and fruit / soft drinks.