Assessing the vulnerability of ML assets and apps

Part of assessing the vulnerabilities of Azure Machine Learning assets involves identifying potential security risks and then implementing appropriate measures to mitigate them.

Here, we will go through Azure Machine Learning components and their possible vulnerabilities. The implementation of security measures will be explained in greater detail in the rest of the book. The assessment is based on the Zero Trust defense areas.

The first step is identifying all the assets associated with Azure Machine Learning, such as data, models, and algorithms. That does not mean the Azure Machine Learning Studio only. Several services associated with Azure Machine Learning need to be checked. Once you have identified the assets, you should assess their potential risks, including unauthorized access, data breaches, and misuse.

It is important to remember that everything in Azure operates on top of cloud infrastructure, so it is helpful to...