Mysql> SELECT gen_dictionary_load('/dict/Lastnames.txt', 'Lastnames')\G Gen_dictionary_load('/dict/Firstnames.txt', 'Firstnames'): Dictionary load success Mysql> SELECT gen_dictionary_load('/dict/Firstnames.txt', 'Firstnames')\G Mysql> SHOW VARIABLES LIKE 'secure_file_priv'\G In order to use data from a dictionary we must first load the data.Ī dictionary is a plain text file, with one term per line: gen_dictionary() : Returns a random term from a dictionary.gen_dictionary_load() : Loads a file into the dictionary registry and assigns the dictionary a name to be used with other functions that require a dictionary name argument.They also start with these 4 first characters: gen_ and you’ll find the complete list here. So another way to generate a relevant dataset is to use dictionaries.Īgain several functions are available. Sometime you will need data with better quality. Generating Random Data Using Dictionaries phone number in the 555 area code not used for legitimate numbers. gen_rnd_us_phone() : returns a random U.S.gen_rnd_pan() : returns a random payment card Primary Account Number.gen_rnd_email() : returns a random email address in the domain.gen_range() : returns a random integer selected from a given range.In this article I’ll use the following functions : They start with these 4 first characters: gen_ and you’ll find the complete list here. Generating Random Data with Specific Characteristics Because it is not always possible to test/simulate your application on your real dataset (indeed playing with customer credit card or security social numbers is a very bad practice) this feature is very convenient. One of the nice “side feature” of MySQL Data Masking and De-Identification is the ability to generate business relevant datasets. INSTALL PLUGIN data_masking SONAME 'data_masking.so' ĬREATE FUNCTION gen_blacklist RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_dictionary RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_dictionary_drop RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_dictionary_load RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_range RETURNS INTEGER SONAME 'data_masking.so' ĬREATE FUNCTION gen_rnd_email RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_rnd_pan RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_rnd_ssn RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION gen_rnd_us_phone RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION mask_inner RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION mask_outer RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION mask_pan RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION mask_pan_relaxed RETURNS STRING SONAME 'data_masking.so' ĬREATE FUNCTION mask_ssn RETURNS STRING SONAME 'data_masking.so' MySQL Enterprise Data Masking and De-Identification, is implemented as a plugin library file containing a plugin and user-defined functions (UDFs). MySQL Enterprise Data Masking and De-Identification is an extension included in MySQL Enterprise Edition, a commercial product.Īvailable in MySQL 8.0, as of 8.0.13 and in MySQL 5.7, as of 5.7.24. “ A built-in database solution to help organizations protect sensitive data from unauthorized uses“ MySQL Enterprise Masking and De-identificaiton protects sensitive data from unauthorized users. The simplest way to present this MySQL feature : MySQL Enterprise Data Masking and De-Identification This the topic of this eight episode of this MySQL Security series (URLs to all the articles at the end of this page). In other words, MySQL Enterprise Data Masking and De-Identification hides sensitive information by replacing real values with substitutes in order to protect sensitive data while they are still look real and consistent. For example, data produced during human subject research might be de-identified to preserve research participants’ privacy. De-identification is the process used to prevent a person’s identity from being connected with information.Data masking or data obfuscation is the process of hiding original data with modified content (characters or other data.). In order to mitigate the effects of data breaches, and therefore the associated risks for your organization’s brand and reputation, popular regulations or standards including GDPR, PCI DSS, HIPAA,… recommand (among others things) data masking and de-identification.
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