Filter Node Module

A library for detecting, parsing, and removing personally identifiable information from strings and objects.

Scenarios

We hope that this software can be useful in some of the following scenarios:

• privacy, security, fraud-detection, and data-auditing
• anonymizing data for research, marketing and machine learning
• accessibility and online guidance
• word tagging and word spotting
• designing chatbots

Languages

pii-filter currently supports the following languages and PII:

• Dutch
  • First Names
  • Family Names
  • Pet Names
  • Medicine Names
  • Phone Numbers
  • Email Addresses
  • Dates

Installing

You can add the pii-filter npm package to your project by running:

npm install --save-dev pii-filter

Documentation

The docs can be read here.

Examples

Sanitizing strings:

import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const raw_str = 'Hallo Johan, mijn 06 is 0612345678, tot morgen.';
const sanitized_str = pii_filter.sanitize_str(raw_str, true);

console.log(sanitized_str);

// output:
'Hallo {first_name}, mijn 06 is {phone_number}, tot morgen.'

Sanitizing objects:

import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const obj =
{
    message: 'Wilma de Vries, 20 november 1964',
    detail: 'Werking Paracetamol bij gebruik medicatie'
};
const sanitized_obj =   pii_filter.sanitize_obj(obj, true, false);

console.dir(sanitized_obj);

// output:
{
    message: '{first_name} {family_name}, {date}',
    detail: 'Werking {medicine_name} bij gebruik medicatie'
}

Parsing PII:

import * as pf from 'pii-filter';

const pii_filter = pf.make_pii_classifier(pf.languages.nl.make_lm());
const raw_str = 'Hallo Johan, mijn e-mail is [email protected] en mijn nummer is 0612345678, tot dan.';
const results = pii_filter.classify(raw_str);

for (let pii of results.pii)
    console.dir(pii);

// output:
{
    value: 'Johan',
    type: 'first_name',
    confidence: 0.755,
    severity: 0.4539742200500001,
    start_pos: 6,
    end_pos: 11
}
{
    value: '[email protected]',
    type: 'email_address',
    confidence: 1,
    severity: 0.2,
    start_pos: 28,
    end_pos: 41
}
{
    value: '0612345678',
    type: 'phone_number',
    confidence: 0.8512500000000001,
    severity: 0.35,
    start_pos: 60,
    end_pos: 70
}  

Main repository

For more information and access to used the datasets check out the main repository.