What is Dynamic Data Masking?
Dynamic Data Masking (DDM) is the practice of obscuring sensitive information within a database, rendering it unintelligible and unreadable when accessed. It involves applying various masking techniques in real-time, dynamically altering sensitive data for users who access it.
Masking methods may vary depending on organizational needs. During masking, either the entire data or specific portions of it can be obfuscated. Common masking techniques include replacing data with static characters (such as asterisks or question marks), tokenization, and encryption. Regardless of the method used, the fundamental objective is to prevent access to sensitive data.
Dynamic Data Masking is widely employed in the digital world today to provide privacy and security. It is particularly favored for preventing direct access to sensitive data by users accessing databases.
The Importance and Advantages of Dynamic Data Masking
Dynamic data masking represents one of the simplest ways to protect sensitive information. By securing sensitive data without making any changes to the underlying data or application settings, it stands as the primary choice for institutions that prioritize security.
Especially for users with direct access to databases like database administrators, application developers, business analysts, etc., openly displaying sensitive data poses various risks concerning security and regulatory compliance. To completely mitigate these risks, dynamic data masking techniques are applied to obscure returned data from tables or columns where sensitive data resides.
It’s crucial to reiterate the significance of data classification processes. To perform masking operations effectively, the correct identification of what needs to be masked should be established. Regular scanning of database objects containing sensitive data through data classification processes and executing masking operations correctly across all environments containing sensitive data are crucial.
It should not be overlooked that every institution harbors independent and unique structures. Therefore, an approach that might be efficient for one institution, even within the same sector, could be inefficient for another. Consequently, identifying the needs and structure of the institution accurately and developing solutions tailored to the institution’s specific requirements is imperative.
At Mernus Information Technologies Inc., we analyze the unique needs of institutions to develop the most suitable data classification and dynamic data masking processes. Don’t hesitate to contact us for such requirements without wasting any time.