Encrypting and securing data
As we saw in the previous section, Azure Machine Learning relies on external services to pull in data as data assets. Depending on the service that hosts the data, there are different security and data protection features we can use, such as encryption, data classification, and data masking.
In this section, we will explore encryption and classification features that relate to our data.
Encryption at rest
Encryption at rest refers to the practice of encrypting data while it is stored or at rest in a storage medium, such as cloud storage. The purpose of encryption at rest is to protect data from unauthorized access if the storage medium is compromised, lost, or stolen.
When data is encrypted at rest, it is transformed into an unreadable form using an encryption algorithm and a cryptographic key. Only authorized users or processes with the proper decryption key can access and decrypt the data to its original readable form. Without the decryption...
