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
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-9 | Version: 0.1.0 | |||
| Draft as of 2023-10-25 | Computable Name: URS_9 | |||
Copyright/Legal: HL7 Europe |
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ID: URS-9
Publisher: HL7 Europe
| Contact Name | Contact Points |
|---|---|
| HL7 Europe |
Description:
Devices used in the Federated Learning process must be secure, regularly patched and protected against malware and other vulnerabilities.
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
Actor for these requirements:
Device
Statements:
ID: URS-9
Label: As a Device, I SHOULD be secure, regularly patched and protected against malware and other vulnerabilities if I'm used in the Federated Learning process.
Sources:
- HL7 Europe
Conformance Requirement SHOULDbe secure, regularly patched and protected against malware and other vulnerabilities if I'm used in the Federated Learning process