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AI Security and Compliance in Azure Flashcards
| Front | Back |
| Define Confidential Computing in Azure. | Protects data in use by executing workloads in secure enclaves on Azure Confidential VMs |
| Describe data minimization for AI solutions. | Collect and process only the data necessary for the AI model reducing privacy risks |
| Explain pseudonymization vs anonymization. | Pseudonymization replaces identifiers with pseudonyms while anonymization irreversibly removes identifiers |
| How can you ensure data residency requirements for AI workloads on Azure? | Deploy resources in specific Azure regions that comply with local data residency laws |
| How can you secure AI model endpoints over the network in Azure? | Use Azure Private Link or deploy endpoints inside an Azure Virtual Network |
| How do Azure Blueprints help in AI compliance? | Provide repeatable templates of Azure resource deployments with built in compliance settings |
| How do managed identities enhance security for Azure AI services? | Provide Azure AD identities for services eliminating the need for credential management |
| How do you audit AI deployments on Azure? | Use Azure Monitor Azure Activity Logs and Azure Audit Logs for tracking changes and access |
| How is data encrypted in transit for Azure AI services? | Transport Layer Security TLS ensures encryption between clients and Azure services |
| Name a CI/CD security practice for MLOps in Azure. | Implement secure pipelines with GitHub Actions Azure DevOps and integrate security scanning of models and containers |
| Name a service for unified data governance and cataloging in Azure. | Azure Purview |
| What Azure feature helps classify and label sensitive data in AI solutions? | Azure Information Protection |
| What encryption options does Azure offer for data at rest in AI workloads? | Azure Storage encryption with Microsoft managed keys Azure Key Vault customer managed keys or Azure Disk Encryption |
| What is differential privacy in the context of Azure AI? | Technique that adds noise to data to protect individual privacy while enabling aggregate analysis |
| What is the purpose of Azure AD role-based access control (RBAC) in AI solutions? | Restricts access to Azure resources by assigning roles and permissions to users groups and applications |
| What is the role of Azure Sentinel in AI security? | Cloud native SIEM for collecting analyzing and responding to security incidents |
| What principles are covered by Azure Responsible AI? | Fairness reliability safety privacy inclusiveness transparency |
| Which Azure feature enforces compliance policies across AI resources? | Azure Policy |
| Which Azure service provides real time threat detection and advanced security for AI environments? | Microsoft Defender for Cloud (formerly Azure Security Center) |
| Which compliance certifications are commonly relevant for AI in Azure? | ISO27001 SOC GDPR HIPAA |
Front
Name a service for unified data governance and cataloging in Azure.
Click the card to flip
Back
Azure Purview
Front
What principles are covered by Azure Responsible AI?
Back
Fairness reliability safety privacy inclusiveness transparency
Front
How can you secure AI model endpoints over the network in Azure?
Back
Use Azure Private Link or deploy endpoints inside an Azure Virtual Network
Front
What is differential privacy in the context of Azure AI?
Back
Technique that adds noise to data to protect individual privacy while enabling aggregate analysis
Front
What is the role of Azure Sentinel in AI security?
Back
Cloud native SIEM for collecting analyzing and responding to security incidents
Front
Explain pseudonymization vs anonymization.
Back
Pseudonymization replaces identifiers with pseudonyms while anonymization irreversibly removes identifiers
Front
Define Confidential Computing in Azure.
Back
Protects data in use by executing workloads in secure enclaves on Azure Confidential VMs
Front
What encryption options does Azure offer for data at rest in AI workloads?
Back
Azure Storage encryption with Microsoft managed keys Azure Key Vault customer managed keys or Azure Disk Encryption
Front
How do you audit AI deployments on Azure?
Back
Use Azure Monitor Azure Activity Logs and Azure Audit Logs for tracking changes and access
Front
How do managed identities enhance security for Azure AI services?
Back
Provide Azure AD identities for services eliminating the need for credential management
Front
How can you ensure data residency requirements for AI workloads on Azure?
Back
Deploy resources in specific Azure regions that comply with local data residency laws
Front
Which Azure service provides real time threat detection and advanced security for AI environments?
Back
Microsoft Defender for Cloud (formerly Azure Security Center)
Front
Which compliance certifications are commonly relevant for AI in Azure?
Back
ISO27001 SOC GDPR HIPAA
Front
Describe data minimization for AI solutions.
Back
Collect and process only the data necessary for the AI model reducing privacy risks
Front
How is data encrypted in transit for Azure AI services?
Back
Transport Layer Security TLS ensures encryption between clients and Azure services
Front
Name a CI/CD security practice for MLOps in Azure.
Back
Implement secure pipelines with GitHub Actions Azure DevOps and integrate security scanning of models and containers
Front
What Azure feature helps classify and label sensitive data in AI solutions?
Back
Azure Information Protection
Front
What is the purpose of Azure AD role-based access control (RBAC) in AI solutions?
Back
Restricts access to Azure resources by assigning roles and permissions to users groups and applications
Front
How do Azure Blueprints help in AI compliance?
Back
Provide repeatable templates of Azure resource deployments with built in compliance settings
Front
Which Azure feature enforces compliance policies across AI resources?
Back
Azure Policy
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This deck highlights security, privacy, and compliance measures related to AI solutions deployed on Azure, including data protection and governance.