Masking data while it is transferred from production systems to test or development systems before the data is saved to disk. This method is convenient for many scenarios but is inherently less secure. For example, the name “John Smith” is always replaced with “Jim Jameson”, everywhere it appears in a database. Involves mapping two sets of data that have the same type of data, in such a way that one value is always replaced by another value. Mage™ brings a static data masking capability that complements Imperva DSF, works across multiple data platforms, and supports flexible deployment mechanisms to integrate seamlessly into the existing enterprise IT framework without the need for any additional architectural changes.ĭownload the Datasheet to learn more. While Imperva Data Security Fabric (DSF) provides real-time protection of live production data, Mage™ de-identifies data in non-production environments. Imperva partners with Mage™ Static Data Masking to deliver SDM capabilities to Imperva customers. The masked copy can then be pushed to the target location. Typically, the process involves creating a backup copy of a database in production, loading it to a separate environment, eliminating any unnecessary data, and then masking data while it is in stasis. The process alters all sensitive data until a copy of the database can be safely shared. Static data masking processes can help you create a sanitized copy of the database. There are several types of data masking types commonly used to secure sensitive data. Can be used for data sanitization – normal file deletion still leaves traces of data in storage media, while sanitization replaces the old values with masked ones.Allows sharing data with authorized users, such as testers and developers, without exposing production data.Makes data useless to an attacker, while maintaining many of its inherent functional properties.Reduces data risks associated with cloud adoption.Data masking solves several critical threats – data loss, data exfiltration, insider threats or account compromise, and insecure interfaces with third party systems.Here are several reasons data masking is essential for many organizations: There are several ways to alter the data, including character shuffling, word or character substitution, and encryption.īlog: The Benefits of Including Static Data Masking in Your Security Arsenal. The goal is to create a version that cannot be deciphered or reverse engineered. The goal is to protect sensitive data, while providing a functional alternative when real data is not needed-for example, in user training, sales demos, or software testing.ĭata masking processes change the values of the data while using the same format. Data masking is a way to create a fake, but a realistic version of your organizational data.
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