DOE · DOE-458 · record R3332
Machine Learning components within CrowdStrike
Department of Energy · SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Overview
- Development stage
- DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- This AI system not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21
- Start date
- 2021-01-27 (day precision)Source: 2021-01-27T00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Cybersecurity
- Operational functions
- Cyber threat detection Derived by keyword rules; see methodology
Problem the AI is intended to solve
CrowdStrike uses machine learning to review security events in order to create notifications of detections and incidents for the SLAC Cybersecurity team.
Expected benefits
From the use of CrowdStrike's machine learning components, SLAC receives the benefit of visibility to analyze possible security events
System outputs
CrowdStrike Detections/Incidents
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- CrowdStrike Falcon
- Custom-developed code
- No
- Public source code
- Not reported
Sourcing
- How it was built
- Purchased from vendorSource: a) Purchased from a vendor
- Vendor (as reported)
- CrowdStrike
- Vendors (standardized)
- CrowdStrike
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Yes
- Demographic features
- k) None of the above
- Training and evaluation data
- CrowdStrike's machine learning model is trained on data generated by activity at SLAC
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported