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Machine Learning Security with Azure

You're reading from  Machine Learning Security with Azure

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781805120483
Pages 310 pages
Edition 1st Edition
Languages
Author (1):
Georgia Kalyva Georgia Kalyva
Profile icon Georgia Kalyva

Table of Contents (17) Chapters

Preface 1. Part 1: Planning for Azure Machine Learning Security
2. Chapter 1: Assessing the Vulnerability of Your Algorithms, Models, and AI Environments 3. Chapter 2: Understanding the Most Common Machine Learning Attacks 4. Chapter 3: Planning for Regulatory Compliance 5. Part 2: Securing Your Data
6. Chapter 4: Data Protection and Governance 7. Chapter 5: Data Privacy and Responsible AI Best Practices 8. Part 3: Securing and Monitoring Your AI Environment
9. Chapter 6: Managing and Securing Access 10. Chapter 7: Managing and Securing Your Azure Machine Learning Workspace 11. Chapter 8: Managing and Securing the MLOps Life Cycle 12. Chapter 9: Logging, Monitoring, and Threat Detection 13. Part 4: Best Practices for Enterprise Security in Azure Machine Learning
14. Chapter 10: Setting a Security Baseline for Your Azure Machine Learning Workloads 15. Index 16. Other Books You May Enjoy

Enhancing access security

Now that we have a better idea of how to leverage Microsoft Entra ID for authentication and role management, we can see some other services that we can use to complement and further secure our users’ identities.

Conditional Access

Conditional Access in Microsoft Entra ID is a powerful feature that allows organizations to set specific conditions and policies for granting or denying access to their cloud-based resources. With Conditional Access, you can create rules and policies that consider a range of factors before allowing or blocking access, enhancing security and compliance.

Conditional Access policies are rules that you define to control access to your protected resources. These policies are based on conditions and can be tailored to specific users, groups, applications, IP location information, user or sign risk detection, and devices. The action based on those signals is either Block/Allow. You can combine multiple conditions based on...

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