Requirements Federated Learning and mUlti-party computation Techniques for prostatE cancer
0.1.0 - ci-build
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
| Official URL: https://flute.com/Requirements/URS-12 | Version: 0.1.0 | |||
| Draft as of 2023-10-25 | Computable Name: URS_12 | |||
Copyright/Legal: HL7 Europe |
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ID: URS-12
Publisher: HL7 Europe
| Contact Name | Contact Points |
|---|---|
| HL7 Europe |
Description:
The exchange of data between data owner nodes and central aggregator should follow the principle of data minimization. Only sharing the necessary data to be able to train models effectively.
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-12
Label: The exchange of data between data owner nodes and central aggregator SHOULD follow the principle of data minimization. Only sharing the necessary data to be able to train models effectively.
Sources:
- HL7 Europe
Conformance Requirement SHOULDfollow the principle of data minimization