Requirements Federated Learning and mUlti-party computation Techniques for prostatE cancer
0.1.0 - ci-build
Funded by the European Union

Requirements Federated Learning and mUlti-party computation Techniques for prostatE cancer, published by HL7 Europe. This guide is not an authorized publication; it is the continuous build for version 0.1.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/hl7-eu/flute-requirements/ and changes regularly. See the Directory of published versions

Requirements: URS-2

Official URL: https://flute.com/Requirements/URS-2 Version: 0.1.0
Draft as of 2023-10-25 Computable Name: URS_2

Copyright/Legal: HL7 Europe

ID: URS-2

Publisher: HL7 Europe

Contact Name Contact Points
HL7 Europe

Description:

Central aggregation of models should not leak any information of the data used to train local models.

Purpose:

Defining the security and privacy requirements for users and stakeholders of the FLUTE platform, which are derived from the threat models and identified attacks within FLUTE.

Copyright Label: Federated Learning and mUlti-party computation Techniques for prostatE cancer


Statements:

ID: URS-2

Label: Central aggregation of models should not leak any information of the data used to train local models.

Sources:

  • HL7 Europe
Conformance Requirement
SHOULD

not leak any information of the data used to train local models