Privacy Preserving Data Processing

On the 9-June-2022 at 11:00 a.m. the 11th lecture of the Living Lab lecture series took place. In this talk, ScaDS.AI scientific researchers Maja Schneider and Anika Hannemann talked about Privacy Preserving Data Processing. Add this event to your calendar (iCal).

In the first part of the lecture, our researchers talked about Privacy-Preserving Data Publishing (PPDP) and illustrated this topic on the example of mobility data by showing its potential but also highlighting the involved privacy risk when such data is being published. Privacy preserving machine learning  (PPML) on the example of decentralised clinical data was the second focus topic of this lecture. PPML is a subdiscipline of Machine Learning that deals with modelling on sensitive data while preserving their privacy. Privacy and a framework for the evaluation of privacy guarantees were defined and, furthermore, an ensemble learning method for modelling on distributed data sets has been introduced.

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Living Lab Lecture Series

The Living Lab Lecture Series gives you an in-depth insight into the many research topics of ScaDS.AI Dresden/Leipzig. From Natural Language Processing to Ethics and Moral Code in AI, a great variety of topics are discussed. You can join our lectures every first thursday of the month or watch them on YouTube afterwards. If you have ideas for topics to discuss in the future, please let our Living Lab team know. We suggest for you to regularly check our event calendar, to never miss out on upcoming lectures or other interesting events organized by or in cooperation with our center.

Find out more about our Living Lab Lecture Series.

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz
Institut
Fraunhofer-Institut
Fraunhofer-Institut
Max-Planck-Institut
Institute
Max-Plank-Institut