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Machine Learning Security with Azure
Machine Learning Security with Azure

Machine Learning Security with Azure: Best practices for assessing, securing, and monitoring Azure Machine Learning workloads

By Georgia Kalyva
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Book Dec 2023 310 pages 1st Edition
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Product Details


Publication date : Dec 28, 2023
Length 310 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120483
Category :
Table of content icon View table of contents Preview book icon Preview Book

Machine Learning Security with Azure

Part 1: Planning for Azure Machine Learning Security

This part is all about creating a plan to secure your resources. Security is organization-specific so you will get an overview of the Zero Trust security approach designed to secure any implementation of IT systems. You will learn to leverage the MITRE ATLAS knowledge base to understand ML attacks. Finally, you will also learn how to develop AI systems ethically and responsibly and how to use Azure services to ensure regulatory compliance.

This part has the following chapters:

  • Chapter 1, Assessing the Vulnerability of Your Algorithms, Models, and AI Environments
  • Chapter 2, Understanding the Most Common Machine Learning Attacks
  • Chapter 3, Planning for Regulatory Compliance
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Key benefits

  • Learn about machine learning attacks and assess your workloads for vulnerabilities
  • Gain insights into securing data, infrastructure, and workloads effectively
  • Discover how to set and maintain a better security posture with the Azure Machine Learning platform
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

With AI and machine learning (ML) models gaining popularity and integrating into more and more applications, it is more important than ever to ensure that models perform accurately and are not vulnerable to cyberattacks. However, attacks can target your data or environment as well. This book will help you identify security risks and apply the best practices to protect your assets on multiple levels, from data and models to applications and infrastructure. This book begins by introducing what some common ML attacks are, how to identify your risks, and the industry standards and responsible AI principles you need to follow to gain an understanding of what you need to protect. Next, you will learn about the best practices to secure your assets. Starting with data protection and governance and then moving on to protect your infrastructure, you will gain insights into managing and securing your Azure ML workspace. This book introduces DevOps practices to automate your tasks securely and explains how to recover from ML attacks. Finally, you will learn how to set a security benchmark for your scenario and best practices to maintain and monitor your security posture. By the end of this book, you’ll be able to implement best practices to assess and secure your ML assets throughout the Azure Machine Learning life cycle.

What you will learn

Explore the Azure Machine Learning project life cycle and services Assess the vulnerability of your ML assets using the Zero Trust model Explore essential controls to ensure data governance and compliance in Azure Understand different methods to secure your data, models, and infrastructure against attacks Find out how to detect and remediate past or ongoing attacks Explore methods to recover from a security breach Monitor and maintain your security posture with the right tools and best practices

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Product Details


Publication date : Dec 28, 2023
Length 310 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120483
Category :

Table of Contents

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

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