Data Privacy by Design and Default
Specification
Develop systems, products, and business practices based upon a principle of privacy by design and industry best practices. Ensure that systems' privacy settings are configured by default, according to all applicable laws and regulations.
Threat coverage
Architectural relevance
Lifecycle
Data collection, Resource provisioning
Design, Guardrails
Evaluation
Orchestration, AI Services supply chain
Operations, Maintenance, Continuous monitoring
Data deletion, Model disposal
Ownership / SSRM
PI
Owned by the Customer (AIC)
The Customer (AIC) is responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies services or products they consume.
Model
Owned by the Customer (AIC)
The Customer (AIC) is responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies services or products they consume.
Orchestrated
Owned by the Customer (AIC)
The Customer (AIC) is responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies services or products they consume.
Application
Owned by the Customer (AIC)
The Customer (AIC) is responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies services or products they consume.
Implementation guidelines
Auditing guidelines
1. Examine whether the CSP’s policy, standards, and procedures create a framework that fosters a culture and expectation of privacy by design. Determine whether this content addresses the directive of the CSP’s culture and whether practices reflect privacy by design and industry best practices. 2. Examine whether the organization’s governance framework, documents, controls, and metrics satisfy the organization, and if its sub-processors comply with this requirement. Establish whether the CSP has documented the roles and responsibilities involved. 3. Obtain and examine supporting documentation maintained as evidence of these metrics to determine if the office or individual responsible reviews the information, and if identified issues were investigated and remediated appropriately. 4. Obtain evidence of the systems' privacy settings and the laws and regulations that apply to the CSP. Determine if the configurations are implemented as defined by the applicable laws and regulations. 5. Verify that processes, systems, and applications used for the collection and processing (including use, disclosure, retention, transmission, and disposal) are limited to what is necessary for the identified purpose. 6. Verify that the CSP limits data collection to the minimum necessary for the identified purposes. 7. Verify that the CSP limits the data processing to what is accurate, adequate, relevant, and necessary for the identified purposes. 8. Verify that the CSP defines and documents data minimization objectives and uses mechanisms (such as de-identification) to meet those objectives. 9. Verify that the CSP either deletes or renders data in a form that does not permit identification when it no longer requires access to identifiable forms of data unless there is a legal requirement or business justification to retain it in identifiable form. 10. Verify that the CSP ensures that temporary files created during data processing are deleted (e.g., erased or destroyed) following documented procedures within a specified, documented time frame. 11. Verify that the CSP does not retain data for longer than necessary for the purposes for which it was processed. 12. Verify that the CSP follows documented policies, procedures, and/or mechanisms when disposing of data. 13. Verify that the CSP subjects data (e.g., sent to another organization) over a data-transmission network to appropriate controls to ensure data reaches its intended destination. 14. Examine the CSP’s policy, standards, and procedures and determine if a culture and expectation of privacy by design for third-party providers is defined. Determine whether this content addresses the directive of the CSP’s culture and whether practices reflect privacy by design and industry best practices. 15. Examine infrastructure design documentation to verify that privacy-enabling capabilities, such as data isolation, segregation mechanisms, and privacy-preserving storage options, are incorporated into the infrastructure architecture. 16. Verify that default configurations for infrastructure components include privacy-enhancing settings such as encryption at rest, secure access controls, and logging that minimizes capture of personal data. 17. Review mechanisms provided to support data residency requirements, confirming the infrastructure enables customers to control where their data is physically stored and processed. 18. Assess how the infrastructure supports privacy compliance through capabilities such as data discovery, classification, pseudonymization, or isolation of regulated information. 19. Verify that infrastructure management interfaces and monitoring tools are designed to minimize the exposure of personal data in logs, alerts, and administrative views by default. 20. Examine how the infrastructure enables secure deletion or isolation of personal data when requested by customers or required by regulations.
Standards mappings
42001: A.2.3 Alignment with other organizational policies 42001: A.5.4 Assessing AI system impact on individuals or groups of individuals 42001: A.6.1.3 Processes for trustworthy AI system design and development 42001: A.6.2.2 AI system requirements and specification 42001: A.6.2.5 AI system deployment 42001: A.6.2.7 AI system technical documentation 42001: A.7.2 Data for development and enhancement of AI system 42001: A.9.3 Objectives for responsible use of AI system 42001: A.7.3 Acquisition of data 27001: A.5.34 - Privacy and protection of personal identifiable information (PII) 27001: A.8.11 - Data masking 27002: 5.34 - Privacy and protection of personal identifiable information (PII) 27002: 8.11 - Data masking
Addendum
N/A
Article 10 Article 52 (1)
Addendum
While under Article 10 (2) (a) privacy principles are covered, default setting specifications aren't detailed.
GV-1.1-001 MS-2.2-002 MS-2.2-003 MS-2.2-004
Addendum
NIST AI 600-1 does not address in a clear manner the DSP-08 topic of using privacy by design principles, but it has loose associations to scattered aspects of this.
No specific mapping.
Addendum
no explicitly mentioned preconfigured hardware
AI-CAIQ questions (2)
Are systems, products, and business practices developed based upon a principle of privacy by design and industry best practices?
Are systems' privacy settings configured by default, according to all applicable laws and regulations?