LIPIcs.GD.2024.2.pdf
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How Can Algorithms Help in Protecting Our Privacy (Invited Talk)
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Monika Henzinger 
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32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: Graph Drawing and Network Visualization (GD) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2024-10-28
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Monika Henzinger. How Can Algorithms Help in Protecting Our Privacy (Invited Talk). In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, p. 2:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.GD.2024.2
https://doi.org/10.4230/LIPIcs.GD.2024.2
Abstract
Decisions are increasingly automated using rules that were learnt from personal data. Thus, it is important to guarantee that the privacy of the data is protected during the learning process. To formalize the notion of an algorithm that protects the privacy of its data, differential privacy was introduced by Dwork, McSherry, Nissim, and Smith in 2006. It is a rigorous mathematical definition to analyze the privacy properties of an algorithm - or the lack thereof. In this talk I will give an introduction to differential privacy with an emphasis on differential private algorithms that can handle dynamically changing input data.
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- Mathematics of computing → Graph algorithms
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