Package Exports

pii-filter

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (pii-filter) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Filter Node Module

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

PII replaced with placeholders

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 test@test.com 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: 'test@test.com',
    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.