Security and Privacy in Federated learning: Challenges and Possible Solutions

Item Type Conference or Workshop Item (Speech)
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.
Authors Mitrokotsa, Katerina
Language English
Subjects computer science
HSG Classification contribution to scientific community
Date July 2022
Event Title Security of Machine Learning
Event Location Schloss Dagstuhl
Event Dates July 10-15, 2022
Depositing User Eriane Breu
Date Deposited 09 Dec 2022 13:21
Last Modified 09 Dec 2022 13:21
URI: https://www.alexandria.unisg.ch/publications/268332

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Mitrokotsa, Katerina: Security and Privacy in Federated learning: Challenges and Possible Solutions. [Conference or Workshop Item]

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https://www.alexandria.unisg.ch/id/eprint/268332
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