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Security and Privacy in Federated learning: Challenges and Possible Solutions
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Security and Privacy in Federated learning: Challenges and Possible Solutions
Type
conference speech
Date Issued
2022-07
Author(s)
Mitrokotsa, Katerina
Abstract
In this talk, we discuss the main security and privacy challenges in federated learning as well as how we may guarantee and secure and private dynamic aggregation of data which can be employed in the federated learning setting.
Language
English
HSG Classification
contribution to scientific community
Event Title
Security of Machine Learning
Event Location
Schloss Dagstuhl
Event Date
July 10-15, 2022
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/108549
Subject(s)
computer science
Division(s)
ICS - Institute of Co...
Eprints ID
268332
File(s)
abstractDagstuhl.pdf (98.17 KB)