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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

Working with the PoLP

As we mentioned in Chapter 1 when we talked about the Zero Trust strategy, we learned about the PoLP, which states that users, devices, and applications should only be granted access to the minimum level of resources necessary to perform their job functions. Users are often given more access privileges to network resources and data, assuming they only access the resources required to perform their daily tasks. However, this tactic imposes a greater risk of unauthorized access. When users have access to resources they don’t need, attackers can take advantage of it. While providing just enough permissions to apps or users to complete their tasks sounds easy, the implementation can present some challenges. Creating overprivileged applications is never the intention, but usually the result of unplanned actions over time.

Overprivileged applications are software applications that have been granted more access rights, permissions, or privileges than they actually...

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