Full data redaction redacts the entire contents of the specified table or view column.

By default the output is displayed as follows:

• Character data types: The output text is a single space.

• Number data types: The output text is a zero (0).

• Date-time data types: The output text is set to the first day of January, 2001, which appears as 01-JAN-01.

Full redaction is the default and is used whenever a Data Redaction policy specifies the column but omits the function_type parameter setting. When you run the DBMS_REDACT.ADD_POLICY procedure, to set the function_type parameter setting for full redaction, you enter the following setting:

function_type    => DBMS_REDACT.FULL

You can use the DBMS_REDACT.UPDATE_FULL_REDACTION_VALUES procedure to change the full redaction output to different values.

In partial data redaction, you redact portions of the displayed output.

You can set the position within the actual data at which to begin the redaction, the number of characters to redact starting from that position, and the redaction character to use. This type of redaction is useful for situations where you want it to be obvious to the person viewing the data that it was redacted in some way. Typically, you use this type of redaction for credit cards or ID numbers.

Be aware that partial data redaction requires that your data width remain fixed. If you want to redact columns containing string values of variable length, then you must use regular expressions.

To specify partial redaction, you must set the DBMS_REDACT.ADD_POLICY procedure function_type parameter to DBMS_REDACT.PARTIAL and use the function_parameters parameter to define the partial redaction behavior.

The displayed output for partial data redaction can be as follows:

• Character data types: When partially redacted, a Social Security number (represented as a hyphenated string within a character data type) with value 987-65-4320 could be redacted so that it is displayed as shown in the following examples. The code on the right specifies how to redact the character data: it specifies the expected input format of the actual data, the format to use for the display of the redacted output, the start position at which to begin the redaction, the character to use for the redaction, and how many characters to redact. The first example uses a predefined format (in previous releases called a shortcut) for character data type Social Security numbers, and the second example replaces the first five numbers with an asterisk (*) while preserving the hyphens (-) in between the numbers.

  XXX-XX-4320    function_parameters => DBMS_REDACT.REDACT_US_SSN_F5,
  
  ***-**-4320    function_parameters => 'VVVFVVFVVVV,VVV-VV-VVVV,*,1,5',
  

• Number data types: The partially redacted NUMBER data type Social Security number 987654328 could appear as follows. Both redact the first five digits. The first example uses a predefined format that is designed for Social Security numbers in the NUMBER data type, and the second replaces the first five numbers with the number 9, starting from the first digit.

  XXXXX4328    function_parameters => DBMS_REDACT.REDACT_NUM_US_SSN_F5,
  
  999994328    function_parameters => '9,1,5',
  

• Date-time data types: Partially redacted datetime values can appear simply as different dates. For example, the date 29-AUG-11 10.20.50.000000 AM could appear as follows. In the first example, the day of the month is redacted to 02 (using the setting d02) and in the second example, the month is redacted to DEC (using m12). The uppercase values show the actual month (M), year (Y), hour (H), minute (M), and second (S).

  02-AUG-11 10.20.50.000000 AM   function_parameters  =>  'Md02YHMS',
  
  29-DEC-11 10.20.50.000000 AM   function_parameters  =>  'm12DYHMS',

Regular expressions redact specific data within a column data value, based on a pattern search.

For example, you can redact the user name of email addresses, so that only the domain shows (for example, replacing hpreston in the email address hpreston@example.com with [redacted] so that it appears as [redacted]@example.com). To perform the redaction, set the DBMS_REDACT.ADD_POLICY procedure function_type parameter to either DBMS_REDACT.REGEXP or DBMS_REDACT.REGEXP_WIDTH, and then use the following parameters to build the regular expression:

• A string search pattern (that is, the values to search for), such as:

  regexp_pattern         => '(.+)@(.+\.[A-Za-z]{2,4})' 
  

  This setting looks for a pattern of the following form:

  one_or_more_characters@one_or_more_characters.2-4_characters_in_range_A-Z_or_a-z
  

• A replacement string, which replaces the value matched by the regexp_pattern setting. The replacement string can include back references to sub-expressions of the main regular expression pattern. The following example replaces the data before the @ symbol (from the regexp_pattern setting) with the text [redacted]. The \2 setting refers to the second match group, which is (.+\.[A-Za-z]{2,4}) from the regexp_pattern setting.

  regexp_replace_string  => '[redacted]@\2'
  

• The starting position for the string search string, such as the first character of the data, such as:

  regexp_position        => DBMS_REDACT.RE_BEGINNING
  

• The kind of search and replace operation to perform, such as the first occurrence, every fifth occurrence, or all of the occurrences, such as:

  regexp_occurrence      => DBMS_REDACT.RE_ALL
  

• The default matching behavior for the search and replace operation, such as whether the search is case-sensitive (i sets it to be not case-sensitive):

  regexp_match_parameter => 'i
  

In addition to the default parameters, you can use a set of predefined formats that enable you to use commonly used regular expressions for telephone numbers, email addresses, and credit card numbers.

In random data redaction, the entire value is redacted by replacing it with a random value.

The redacted values displayed in the result set of the query change randomly each time application users run the query.

This type of redaction is useful in cases where you do not want it to be obvious that the data was redacted. It works especially well for number and datetime data types, where it is difficult to distinguish between random and real data.

The displayed output for random values changes based on the data type of the redacted column, as follows:

• Character data types: The random output is a mixture of characters (for example, HTU[G{\pjkEWcK). It behaves differently for the CHAR and VARCHAR2 data types, as follows:

  • CHAR data type: The redacted output is always in the same character set as the character set of the column. The byte length of the redacted output is always the same as the column definition length (that is, the column length that was provided at the time of table creation). For example, if the column is CHAR(20), then a string of 20 random characters is provided in the redacted output of the user's query.

  • VARCHAR2 data type: For random redaction of a VARCHAR data type, the redacted output is always in the same character set as the character set of the column. The length of the redacted output is limited based on the length of the actual data in the column. No characters in excess of the length of the actual data are displayed. For example, if the column is VARCHAR2(20) and the row being redacted contains actual data with a length of 12, then a string of 12 random characters (not 20) is provided in the redacted output of the user's query for that row.

• Number data types: Each actual number value is redacted by replacing it with a random, non-negative number modulo the absolute value of the actual data. This redaction results in random numbers that do not exceed the precision of the actual data. For example, the number 987654321 can be redacted by replacing it with any of the numbers 12345678, 13579, 0, or 987654320, but not by replacing it with any of the numbers 987654321, 99987654321, or -1. The number -123 could be redacted by replacing it with the numbers 122, 0, or 83, but not by replacing it with any of the numbers 123, 1123, or -2.

  The only exception to the above is when the actual value is an integer between -1 and 9. In this case, the actual data is redacted by replacing it with a random, non-negative integer modulo ten (10).

• Date-time data types: When values of the date data type are redacted using random Data Redaction, Oracle Database displays them with random dates that are always different from those of the actual data.

The setting for using random redaction is as follows:

function_type    => DBMS_REDACT.RANDOM

The full, partial, and random data redaction styles affect the Oracle built-in, ANSI, user-defined, and Oracle supplied types in different ways.

• Oracle Built-in Data Types Redaction Capabilities
  Oracle Data Redaction handles the Oracle built-in data types depending on the type of Data Redaction policies that are used.
• ANSI Data Types Redaction Capabilities
  Oracle Data Redaction converts ANSI data types in specific ways, depending on the type of redaction that the Data Redaction policy has.
• Built-in and ANSI Data Types Full Redaction Capabilities
  For full redaction, the default redacted value depends on whether the data type is Oracle built-in or ANSI.
• User-Defined Data Types or Oracle Supplied Types Redaction Capabilities
  Several data types or types are not supported by Oracle Data Redaction.

You can create a Data Redaction policy that does not perform redaction.

This is useful for cases in which you have a redacted base table, yet you want a specific application user to have a view that always shows the actual data. You can create a new view of the redacted table and then define a Data Redaction policy for this view. The policy still exists on the base table, but no redaction is performed when the application queries using the view as long as the DBMS_REDACT.NONE function_type setting was used to create a policy on the view.