Using Microsoft Azure Security Tools to Protect AI Solutions

As more and more systems are automated with the use of AI, securing AI solutions is of paramount importance. In this course, you will explore the various facilities Azure offers to secure Azure machine service learning solutions.
Course info
Level
Intermediate
Updated
Jun 26, 2019
Duration
1h 45m
Table of contents
Description
Course info
Level
Intermediate
Updated
Jun 26, 2019
Duration
1h 45m
Description

Securing AI solutions is of paramount importance; not only can AI solutions be hacked, they can be used to hack other systems. In this course, Using Microsoft Azure Security Tools to Protect AI Solutions, you'll explore how AI and security introduce new challenges that we conventionally did not have to worry about. You'll then learn about the various facilities Azure offers that work with Azure ML workspace in helping you secure your AI solutions. Finally, you'll review the various facets you need to consider and the various processes and artifacts you must secure. By the end of this course, you will have a clear vision and understand the various building blocks required to secure Azure AI solutions.

About the author
About the author

Sahil Malik has been a Microsoft MVP for the past 8 years, author of several books and numerous articles in both the .NET and SharePoint space, consultant and trainer who delivers talks at conferences internationally.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hello. My name is Sahil Malik, and welcome to my course, Using Microsoft Azure Security Tools to Protect AI Solutions. As we move forward in time, more and more solutions will be automated through AI. Certainly, this has great potential to both help and hurt humanity. It all depends on how we manage and secure it. Security therefore is extremely important in AI projects because it's not just a matter of securing the AI solution itself. AI solutions can be used to hack other non-AI solutions, and the attack vectors are also very interesting. In this course, I explain the nature of attacks in AI-based projects. I then explain the various Azure facilities that Azure Machine Learning service builds upon. I explain concepts such as role-based security in an Azure machine learning service, the roles managed identities play, securing your scoring endpoints, and so much more. While security is a pretty big topic, at the end of this course, you will have a clear vision of the various vectors you need to protect in your AI projects and how the various facilities in Azure can help you do so. I hope you find this course useful, and thank you very much for watching!