Data Masking solutions refer to software tools and techniques used to protect sensitive data by replacing it with fictitious but realistic data.
This category includes various solutions designed to safeguard sensitive information from unauthorized access or misuse. These solutions typically employ data obfuscation techniques to ensure that the masked data remains usable for testing, development, or analytics purposes while maintaining its confidentiality.
Key features of data masking solutions may include:
-Dynamic data masking to provide real-time masking of sensitive data during application runtime.
-Static data masking of data at rest in non-production environments.
-Tokenization to replace sensitive data with randomly generated tokens.
-Encryption that transforms data into an unreadable format using encryption algorithms.
-Anonymization to remove personally identifiable information from datasets.
-Data scrambling, where data values are shuffled or randomized values while preserving their format.
-Data subsetting for testing or development purposes.
-Data masking policies for masking specific data elements.
-Audit and compliance for data access and masking activities.