Machine Learning Bill of Materials (ML-BOM)

 

Model and dataset transparency for security, privacy, safety and ethical considerations

Software Bill of Materials
Software-as-a-Service BOM
Vulnerability Exploitability Exchange
Hardware Bill of Materials
Operations Bill of Materials
Vulnerability Disclosure Report
Javascript Object Notation
Extensible Markup Language
Protocol Buffers

ML-BOMs provide transparency for machine learning models and datasets, which provide visibility into possible security, privacy, safety, and ethical considerations. CycloneDX standardizes model cards in a way where the inventory of models and datasets can be used independently or combined with the inventory of software and hardware components or services defined in HBOMs, SBOMs, and SaaSBOMs.

High-Level Object Model

CycloneDX Object Model Swimlane

See also

Additional Capabilities

CycloneDX Supporters

Apiiro
Contrast Security
Ecma International
Fortress Information Security
IBM
IonChannel
Kondukto
Lockheed Martin
NowSecure
OWASP
Rezilion
ServiceNow
Sonatype