PostgreSQL Anonymizer 0.5: Generalization and k-anonymity

Eymoutiers, France, November 6, 2019

Postgresql Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The extension supports 3 different anonymization strategies: Dynamic Masking, In-Place Anonymization and Anonymous Dumps. It also offers a large choice of Masking Functions: Substitution, Randomization, Faking, Partial Scrambling, Shuffling, Noise Addition and Generalization.

Generalization

The idea of generalization is to replace data with a broader, less accurate value. For instance, instead of saying "Bob is 28 years old", you can say "Bob is between 20 and 30 years old". This is interesting for analytics because the data remains true while avoiding the risk of re-identification.

PostgreSQL can handle generalization very easily with the RANGE data types, a very poweful way to store and manipulate a set of values contained between a lower and an upper bound.

Here's a basic table containing medical data:

sql SELECT * FROM patient; ssn | firstname | zipcode | birth | disease
-------------+-----------+---------+------------+--------------- 253-51-6170 | Alice | 47012 | 1989-12-29 | Heart Disease 091-20-0543 | Bob | 42678 | 1979-03-22 | Allergy 565-94-1926 | Caroline | 42678 | 1971-07-22 | Heart Disease 510-56-7882 | Eleanor | 47909 | 1989-12-15 | Acne

We want the anonymized data to remain true because it will be used for statistics. We can build a view upon this table to remove useless columns and generalize the indirect identifiers (zipcode and birthday):

sql CREATE MATERIALIZED VIEW generalized_patient AS SELECT 'REDACTED'::TEXT AS firstname, anon.generalize_int4range(zipcode,1000) AS zipcode, anon.generalize_daterange(birth,'decade') AS birth, disease FROM patient;

This will give us a less accurate view of the data:

sql SELECT * FROM generalized_patient; firstname | zipcode | birth | disease
-----------+---------------+-------------------------+--------------- REDACTED | [47000,48000) | [1980-01-01,1990-01-01) | Heart Disease REDACTED | [42000,43000) | [1970-01-01,1980-01-01) | Allergy REDACTED | [42000,43000) | [1970-01-01,1980-01-01) | Heart Disease REDACTED | [47000,48000) | [1980-01-01,1990-01-01) | Acne

k-anonymity

k-anonymity is an industry-standard term used to describe a property of an anonymized dataset. The k-anonymity principle states that within a given dataset, any anonymized individual cannot be distinguished from at least k-1 other individuals. In other words, k-anonymity might be described as a "hiding in the crowd" guarantee. A low value of k indicates there's a risk of re-identification using linkage with other data sources.

You can evaluate the k-anonymity factor of a table in 2 steps :

  1. First defined the columns that are [indirect idenfiers] ( also known as "quasi identifers") like this:

```sql SECURITY LABEL FOR anon ON COLUMN generalized_patient.zipcode IS 'INDIRECT IDENTIFIER';

SECURITY LABEL FOR anon ON COLUMN generalized_patient.birth IS 'INDIRECT IDENTIFIER'; ```

  1. Once the indirect identifiers are declared :

sql SELECT anon.k_anonymity('generalized_patient')

In the example above, the k-anonymity factor of the generalized_patient materialized view is 2.

Lorem Ipsum

For TEXT and VARCHAR columns, you can now use the classic Lorem Ipsum generator:

  • anon.lorem_ipsum() returns 5 paragraphs
  • anon.lorem_ipsum(2) returns 2 paragraphs
  • anon.lorem_ipsum( paragraphs := 4 ) returns 4 paragraphs
  • anon.lorem_ipsum( words := 20 ) returns 20 words
  • anon.lorem_ipsum( characters := 7 ) returns 7 characters

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

On Red Hat / CentOS systems, you can install it from the official PostgreSQL RPM repository:

$ yum install postgresql_anonymizer12

Then add 'anon' in the shared_preload_libraries parameter of your postgresql.conf file. And restart your instance.

For other system, check out the install documentation :

https://postgresql-anonymizer.readthedocs.io/en/latest/INSTALL/

WARNING: The project is at an early stage of development and should be used carefully.

Thanks

This release includes code and ideas from Travis Miller, Jan Birk and Olleg Samoylov. Many thanks to them !

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. We need your feedback and ideas ! Let us know what you think of this tool, how it fits your needs and what features are missing.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs


PostgreSQL Anonymizer 0.4 : Declare Masking Rules With Security Labels

Eymoutiers, October 14, 2019

Postgresql Anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

This new version introduces a major change of syntax. In the previous versions, the data masking rules were declared with column comments. They are now defined by using security labels:

sql SECURITY LABEL FOR anon ON COLUMN customer.lastname IS 'MASKED WITH FUNCTION anon.fake_last_name()'

The previous syntax is still supported and backward compatibility is maintained.

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

It requires extension named tsm_system_rows (available in the contrib package) and an extension called ddlx (available via PGXN) :

$ pgxn install ddlx $ pgxn install postgresql_anonymizer

Then add 'anon' in the shared_preload_libraries parameter of your postgresql.conf file. And restart your instance.

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. We need your feedback and ideas ! Let us know what you think of this tool, how it fits your needs and what features are missing.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs


PostgreSQL Anonymizer 0.3 : In-Place Masking and Anonymous Dumps

Paris, August 26, 2019

postgresql_anonymizer is an extension that hides or replaces personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

Firts of all, you declare a list of Masking Rules directly inside the database model with SQL comments like this :

COMMENT ON COLUMN users.name IS 'MASKED WITH FUNCTION md5(name)';

Once the masking rules are declared, anonymization can be acheived in 3 different ways:

In addition, various Masking Functions are available : randomization, faking, partial scrambling, shuffling, noise, etc... You can also user your own custom function !

For more detail, please take a look at the documention: https://postgresql-anonymizer.readthedocs.io/

How to Install

This extension is officially supported on PostgreSQL 9.6 and later.

It requires extension named tsm_system_rows (available in the contrib package) and an extension called ddlx (available via PGXN) :

$ pgxn install ddlx $ pgxn install postgresql_anonymizer

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

PostgreSQL Anonymizer is part of the Dalibo Labs initiative. It is mainly developed by Damien Clochard.

This is an open project, contributions are welcome. We need your feedback and ideas ! Let us know what you think of this tool, how it fits your needs and what features are missing.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/dalibo/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs


Introducing PostgreSQL Anonymizer 0.2.1 !

Paris, october 29, 2018

postgresql_anonymizer is an extension to mask or replace personally identifiable information (PII) or commercially sensitive data from a PostgreSQL database.

The projet is aiming toward a declarative approach of anonymization. This means we're trying to extend PostgreSQL's Data Definition Language (DDL) in order to specify the anonymization strategy inside the table definition itself.

The extension can be used to put dynamic masks on certain users or permanently modify sensitive data. Various masking techniques are available : randomization, partial scrambling, custom rules, etc.

This tool is distributed under the PostgreSQL licence and the code is here:

https://gitlab.com/daamien/postgresql_anonymizer

Example

Imagine a people table

sql =# SELECT * FROM people; id | name | phone ------+----------------+------------ T800 | Schwarzenegger | 0609110911

STEP 1 : Activate the masking engine

sql =# CREATE EXTENSION IF NOT EXISTS anon CASCADE; =# SELECT anon.mask_init();

STEP 2 : Declare a masked user

sql =# CREATE ROLE skynet; =# COMMENT ON ROLE skynet IS 'MASKED';

STEP 3 : Declare the masking rules

```sql =# COMMENT ON COLUMN people.name IS 'MASKED WITH FUNCTION anon.random_last_name()';

=# COMMENT ON COLUMN people.phone IS 'MASKED WITH FUNCTION anon.partial(phone,2,$$**$$,2)'; ```

STEP 4 : Connect with the masked user

sql =# \! psql test -U skynet -c 'SELECT * FROM people;' id | name | phone ------+----------+------------ T800 | Nunziata | 06******11

How to Install

This extension is officially supported on PostgreSQL 9.6 and later. It should also work on PostgreSQL 9.5 with a bit of hacking.

It requires an extension named tsm_system_rows, which is delivered by the postgresql-contrib package of the main linux distributions

You can install it with pgxn or build from source it like any other extenstion.

WARNING: The project is at an early stage of development and should be used carefully.

How to contribute

I'd like to thanks all my wonderful colleagues at Dalibo for their support and especially Thibaut Madelaine for the initial ideas.

This is an open project, contributions are welcome. I need your feedback and ideas ! Let me know what you think of this tool, how it fits your needs and what features are missing.

If you want to help, you can find a list of Junior Jobs here:

https://gitlab.com/daamien/postgresql_anonymizer/issues?label_name%5B%5D=Junior+Jobs