Data masking

Dynamic Data Masking in SQL Server

February 2, 2021 by Dinesh Asanka

Introduction

In this article, we will be looking at how to perform and access Dynamic Data Masking in SQL Server. Data Masking is the process of hiding data with different rules. One of the main reasons to apply data masking is to protect Personal Identifiable Information (PII) and sensitive data from unauthorized access. Even when unauthorized users access these data, they will not be able to view the actual values. This article will look at the possibilities of applying Dynamic Data Masking in SQL Server and we will look at how Dynamic Data masking can be applied to the Azure SQL Databases as well.

Data Masking or Altering Behavioral Information

June 26, 2020 by Timothy Smith

As tracking behavioral data becomes increasingly popular, firms may overlook areas where they can collect the same information while data masking details that can be used in a compromise. Behavioral data collection can be extremely dangerous as it allows attackers a wide range of attacks, from spoofing targets to automating custom attacks on targets. Since behavior can reveal key details about us, this information may be as costly as private identifiable information. When tracking behavioral data, we want to weigh risks, and, in some cases, we can accomplish the same result without specific details. In other cases, we may want to mask specific behavioral information on reports that are generated, even if we retain the specific time. We’ll look at a method where we can accomplish either – updating data to remove time or data masking specific time while returning the information we want.

Enterprise Data Masking in MySQL

April 15, 2020 by Nisarg Upadhyay

In this article, I am going to explain Data Masking feature in MySQL. The data masking is the MySQL enterprise edition feature. You can download the trial version of MySQL enterprise edition from here. Data Masking is a process of hiding confidential data like credit card information, SSNs, addresses etc. to safeguard sensitive data.

Understanding Dynamic Data Masking in SQL Server

April 2, 2020 by Aveek Das

In this article, I’m going to explain the Dynamic Data Masking feature in SQL Server. As it goes by the name, Dynamic Data Masking is one of the security features that was introduced in SQL Server 2016. In an ever-growing digital era, the security of ones’ data has become one of the most important and expensive deals. Everyone expects their data to be protected as their own asset and like to treat it with the highest efficiency possible.

Dynamic Data Masking In SQL Server

October 15, 2019 by Ben Richardson

Security has been one of the prime concerns of database developers since the inception of database management systems. Various data protection schemes have been introduced to provide secure access to sensitive data.

Implementing Dynamic Data Masking in Azure SQL database

July 30, 2019 by Ranga Babu

In this article, we will review Dynamic Data Masking in the Azure SQL database. Dynamic Data Masking is a feature to limit the sensitive data to the non-privileged users by hiding the data of a column. Data is not masked and stored in the disk. Masking is applied to the result set returned to the user. The users with “db_owner” permission on “UNMASK” permission can still see the unmasked data when they query the table.

Static Data Masking in SSMS 18

December 6, 2018 by Rajendra Gupta

In this article we are going to talk about Static Data Masking, a new feature for the SQL Databases in SSMS. Static Data Masking feature previously was available only for the Azure SQL DB.

Using Dynamic Data Masking in SQL Server 2016 to protect sensitive data

October 17, 2016 by Ahmad Yaseen

Dynamic Data Masking is a new security feature introduced in SQL Server 2016 that limits the access of unauthorized users to sensitive data at the database layer.

As an example of the need for such a feature is allowing the applications developers to access production data for troubleshooting purposes and preventing them from accessing the sensitive data at the same time, without affecting their troubleshooting process. Another example is the call center employee who will access the customer’s information to help him in his request, but the critical financial data, such as the bank account number or the credit card full number, will be masked to that person.