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Overview

An entity type is what DryvIQ is detecting. The DryvIQ Platform comes with preinstalled entity types that cover a wide range of data, but you also have the option to create custom entity types. Entity types are assigned to a category that identifies the type of data being detected and a match type that identifies how the data is being detected. This page provides a high-level overview to help you understand entity types. To learn more about a specific match type, refer to the DryvIQ Platform documentation page for that specific match type.

Categories

Categories identify the type of data being detected. DryvIQ comes with the default categories listed below. You can also create custom categories if one of the default categories doesn’t capture what your entity type will be identifying. (See Managing Categories for information about creating and managing custom categories.)

Category

Description

1

AI Classifier

This category includes entity types that use DryvIQ’s Artificial Intelligence (AI) engine to classify documents. These include

  • Form matcher

  • File Name classifier

  • Document Type classifier

  • Language Detection

  • Sensitive Object Detector.

2

File Details

These entity types leverage file details to classify documents.

3

Finance

These entity types are for financial information such as

  • ABA routing numbers

  • credit card numbers

  • bank account numbers.

4

General

This is a catch-all category for any entity type that doesn’t fall into one of the other four categories. Custom entity types are assigned to this category.

5

HR

These entity types identify information commonly found in documents for Human Resources such as

  • Compensation

  • Date of birth

  • Disability status

  • Employee identification numbers

  • Disability status

  • Hire date

  • Marital status

  • Military and Veteran status

  • Termination date

  • Vaccination status

6

International Drivers License

These entity types use regular expression to identify driver’s license numbers for specific countries.

7

Metadata

These entity types leverage file metadata to classify documents.

8

PII

This entity type can identify personally identifiable information (PII) in a document.

9

Privacy

This category is for any entity type pertaining to personally identifiable information (PII). Examples of this type of information include

  • Email addresses

  • Healthcare and Insurance related numbers

  • National identification numbers for various countries

  • Passport numbers,

  • phone numbers,

  • U.S. driver’s license numbers

  • U.S. social security numbers

10

Regulation

Regulation entity types identify information that is generally associated with regulatory agencies as

  • Ethnic and Racial characteristics

  • Gender identities

  • General Data Protection Regulation (GDPR) keywords for travel, banking, government identification, and personal identification

  • Geolocation

  • Religious and philosophical characteristics

  • Sexual orientation

  • Trade union memberships

11

Technology

This category includes entity types related to the technology field such as

  • API keys

  • Client and platform IDs

  • Client secrets

  • Domain names

  • International Mobile Equipment Identity numbers

  • IP addresses

  • MAC addresses

  • Passwords

  • Product license keys

  • User IDs

12

US Drivers Licenses

These entity types identify driver’s license numbers for each state in the Unites States of America.

Match Type

Match type is how the data is being detected. DryvIQ supports four match type methods.

Match Type

Description

1

Block List

A block list allows matching on a given list of keywords within a piece of content. 

2

Classification

This is a custom classification model that is plugged into the system. DryvIQ has the following preinstalled classification entity types:

  1. Document Type

  2. File Name

  3. Form Matcher

  4. Language Detection

  5. Microsoft Information Protection

  6. PII Extraction Module

  7. Sensitive Object Detector

3

Regular Expression

Regular expression is a pattern used to identify text. It allows you to have very fine-grained control over what content DryvIQ detects.

4

Transformation

A transformation entity type allows for applying a custom metadata expression against any prior matches to generate new value. This option is available only through the DryvIQ API.

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