File Masking Overview
Description
GenRocket uses Synthetic Data Masking (SDM) to replace sensitive data with synthetic values in files. The synthetically generated values have similar characteristics to the real value but cannot be traced back because they are synthetic. SDM maintains the data structure, ensuring usability. GenRocket provides File Masking Receivers for this purpose, which can also be used to mask sensitive data in NoSQL databases.
Available File Masking Receivers
GenRocket provides file masking capabilities through Receivers for the following data types:
|
File Type |
Masking Receiver |
Description |
| Delimited Files | DelimitedFileMaskReceiver | Masks targeted sensitive values within a delimited file (e.g., CSV, TXT). |
| Excel Files | ExcelFileMaskReceiver | Masks targeted sensitive values within an Excel file using Synthetic Data Replacement (SDR). |
| Fixed File | FileMaskMultiBlockReceiver | Masks targeted sensitive values within a fixed file (e.g., VSAM). |
| JSON | JSONFileMaskReceiver | Masked targeted, sensitive values within a template JSON file with synthetic data values in a new JSON file. |
| Parquet | ParquetFileMaskReceiver | Mask targeted Attributes (columns) within a given Parquet file using Synthetic Data Replacement (SDR). |
| XML | XMLFileMaskReceiver | Masks targeted sensitive node(s) within a source XML file with synthetic values in a new XML file. |
| ORC (Hadoop) | ORCFileMaskReceiver | Masks targeted Attributes (i.e., columns) within a given ORC (Hadoop) file. |
| EDI | EDIFileMaskReceiver | Uses an existing EDI document as a template to create one or more EDI documents by replacing the sensitive data with synthetically generated data at the positions configured in the Receiver. |
GenRocket also offers data subsetting and masking capabilities for supported databases. For more information, see Synthetic Data Masking (SDM) and Data Subsetting Overview.
How to Use File Masking Receivers
Each of the above file masking receivers works slightly differently, but they have a similar pattern of steps.
- Create a Project with the Default Project Version
- Create a Default Domain and Add Attributes
- Define the Masking Receiver Parameters
- Create a Default Scenario
- Download the Scenario and Execute
Using File Masking for NoSQL Databases
Data can also be masked for NoSQL databases by exporting the data to a file such as JSON. Once exported, a File Masking Receiver can mask sensitive data values. You can then insert the masked data file into the NoSQL database.
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