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Sellami et al., 2023 - Google Patents

Interaction Patterns for Regulatory Compliance in Federated Learning.

Sellami et al., 2023

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Document ID
18184516567789480183
Author
Sellami M
Momcilovic T
Kuhn P
Balta D
Publication year
Publication venue
CIISR@ Wirtschaftsinformatik

External Links

Snippet

Organizations in highly regulated domains often struggle to build well-performing machine learning (ML) models due to restrictions from data protection regulation. Federated learning (FL) has recently been introduced as a potential remedy, whereby organizations share local …
Continue reading at repo.bibliothek.uni-halle.de (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60Protecting data
    • G06F21/62Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31User authentication
    • G06F21/34User authentication involving the use of external additional devices, e.g. dongles or smart cards

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