Are you looking for details about Dynamic Data Masking? Are you also interested in knowing what are the things we need to consider for implementing Dynamic Data Masking also known as DDM? If so, then you reached the right place. In this article, we will explore various aspects of Dynamic Data Masking.
A) What is Dynamic Data Masking (DDM)?
Dynamic Data Masking is a technology using which we can mask production data in real-time. Dynamic Data Masking also called DDM does not change data physically. DDM just changes the data stream in order to mask the sensitive data when the requestor request such information.
B) What are the Dynamic Data Masking tools?
Various vendors provide Dynamic Data Masking functionalities and these are
1. Microsoft Azure SQL Database
2. Oracle Enterprise Manager
3. iMask
4. Informatica Dynamic Data Masking
5. Imperva Data Masking
6. Infosphere Optim Data Privacy by IBM
7. K2 view Data Masking
8. Mentis
C) What are data masking Rules?
The rules contain various conditions and actions that rule engines use in order to process the request.
e.g.
1) Connection rules : It process application connection requests.
2) Security rules : It process SQL statements.
Here are important points about rules
a) We can define and create rules in order to process SQL requests that are executed by an application against the database.
b) DDM rule uses two techniques i.e connection criteria and masking techniques.
c) In order to forward the requests the rule Engine uses connection criteria.
d) In order to mask the data the masking technique is used.
D) What are DDM rule components?
The DDM rule components are as below
a) Matcher: It defines the criteria for the rule engine to identify the match.
b) Action: It defines action which will be applied by the rule engine to request.
c) Processing Action: The rule engine applies specific action to the request after applying the rule.
Learn more about Dynamic Data Masking here
No comments:
Post a Comment
Please do not enter any spam link in the comment box.