Data security has traditionally been seen as a matter of locking down data in a physical location, such as a data center. But as data migrates across networks, borders, mobile devices, and into the cloud and Internet of Things (IoT), focusing solely on the physical location of data is no longer relevant.
To prevent disclosure of sensitive corporate data to unauthorized people in this new corporate environment, data needs to be secured. Encryption and data masking are two primary ways for securing sensitive data, either at rest or in motion, in the enterprise. They are important parts of endpoint security and any enterprise’s optimal security posture.
Encryption is the process of encoding data in such a way that only authorized parties can access it. Using homomorphic encryption, sensitive data in plaintext is encrypted using an encryption algorithm, generating cipher text that can only be read if decrypted.
In data masking, “fake” data replaces real data for users who should not have access to the real data, whether because of their role in the company or because they are attackers. Masking ensures sensitive data is obscured or otherwise de-identified.
Dynamic data masking can transform the data based on the user roles and privileges. It is used to secure real-time transactional systems and improve data privacy, compliance implementation, and maintenance.
With data masking, data is retained in its native form, and no decryption key is necessary. The resulting data set does not contain any references to the original information, making it useless for attackers.