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anonymize-personal-data

v1.0.5

Published

A tool to anonymize personal data. This is usefull when you want to send your data to an external services (like api.ai) without exposing your user true data.

Downloads

2

Readme

Anonymize

A tool to anonymize personal data. This is usefull when you want to send your data to an external services (like api.ai) without exposing your user true data.

Installation

 npm install anonymize-personal-data --save

Example of Usage

var Anonymize = require('anonymize-personal-data');
 
var anonymizedData = 
  Anonymize.removePersonalData("Je vais a Paris ce weekend et mon email est [email protected]", "fr");
 
var unAnoymizedData = Anonymize.restorePersonalData(anonymizedData.text, anonymizedData.data);
 
console.log(anonymizedData, unAnoymizedData);

Reference

This module contain 2 methods :

removePersonalData

This method take a string in entry and a local and return an object with a text field containing an anonymized string

var data =  Anonymize.removePersonalData("STRING", "local");
console.log(data)

restorePersonalData

This method allow for easy de-anonynization of a string.

var originalString = Anonymize.restorePersonalData(anoymizedData.text, anoymizedData.data);

Language support

For now the tool support the local 'fr' (France) with the following data :

  • All French name and lastname according to insee
  • All French City name
  • All French zipcode
  • All French Phone number
  • All email address
  • French Vehicule registration number
  • French National healthcare number (SECU)

For now the tool support the local 'uk' (United Kingdom) with the following data :

  • UK name and lastname according to internet
  • All UK Town name
  • All UK County name
  • All UK zipcode
  • All UK Phone number
  • All email address
  • UK Vehicule registration number
  • UK National healthcare number (NIH)
  • UK VAT numbers
  • UK Child Benefits Regference number

Extending to more language / type of data

To add a new local, create a new directory in dictionary named with local name. Then add in this directory some list or regexp file. List files are list of keyword to replace, separate by a \n (ex : city name). Regexp files contain a regexp matching a data you want to replace (ex : email address)