Create custom sensitive information types with exact data match

Microsoft provides various tools and services to help organizations protect their sensitive information. In the world of increasing digital threats, it’s crucial for businesses to ensure that the sensitive data they hold is secure from unauthorized access. When preparing for the SC-400 Microsoft Information Protection Administrator exam, understanding how to create custom sensitive information types with Exact Data Match (EDM) is an important aspect.

What is Exact Data Match?

Exact Data Match is an advanced data protection feature that enhances the existing sensitive information types in Microsoft 365 by enabling you to identify and protect sensitive items more accurately. This is particularly useful when you have specific patterns of data unique to your organization – like customer IDs, medical records, or other forms of structured sensitive information.

Defining a Sensitive Information Type

To begin with, you need to define a sensitive information type. You would do this by creating a schema within the Security & Compliance Center. The schema informs the EDM system about the structure of the sensitive data you want to protect, specifying elements such as the primary key and other fields within your sensitive data table.

Here is a simplified example of defining a schema that might be used to protect customer information:

Creating a Hashed Data Store

After defining the schema, the next step involves creating a hashed data store. The data store is a secure and hashed representation of the actual data you want to protect. You would upload the sensitive information into this store where it’s hashed on-premises before being sent to Azure. This ensures that not even Microsoft can view your sensitive data in its original form.

Creating Custom Sensitive Information Types

Next, create the custom sensitive information type in the Microsoft 365 compliance center. This process includes writing rules and confidence levels designed around finding the types of sensitive information specific to your organization’s needs. These rules could involve regular expressions (regex), keywords, and other matching elements that will trigger when the exact type of data you are trying to protect is detected.

For example, you might create a rule for detecting customer records that includes the CustomerID and SSN:

Rule:
– Support regex matching for CustomerID
– Keyword proximity (e.g., the word “customer” within 30 characters of a detected SSN)
– Confidence Level: 85%

This rule would tell the system to look for instances where specific patterns or keywords identified as sensitive appear close to each other, allowing for better precision in detecting when sensitive data is in danger of being exposed.

Benefits of Implementing EDM

Implementing Exact Data Match allows you to set up a customized sensitive information type that reduces false positives and increases efficiency in data loss prevention (DLP) policies. When defining DLP policies using your custom sensitive information types, you can be more precise about what information is allowed to be shared and with whom.

Additionally, EDM serves as a more efficient way to manage personally identifiable information (PII), protected health information (PHI), and other specialized personal data sets in compliance with regulations such as GDPR, HIPAA, and more.

Conclusion

In conclusion, developing custom sensitive information types with Exact Data Match is a powerful capability for protecting sensitive information. For an SC-400 exam candidate, understanding how to set up, manage, and fine-tune these types of sensitive information types is key to ensuring comprehensive protection and adherence to various compliance requirements. Utilizing Exact Data Match helps organizations keep their critical information secure by allowing for more precise detection and protection mechanisms.