Each filter is capable of identifying and redacting a specific type of sensitive information. For example, there is a filter for phone numbers, a filter for US social security numbers, and a filter for person’s names. You can enable any combination of these filters based on the types of sensitive information you need to redact. This section of the documentation describes the available filters and how to enable and configure each.
Predefined Filters
Many predefined types of sensitive information can be identified and redacted. Each type, or filter, can be enabled or disabled separately from the other types in a filter profile.
Person’s Names
Several methods are utilized to identify person’s names.
| Type | Description |
|---|---|
| Person’s Names | Identifies full names using natural language processing analysis methods. |
| First Names | Identifies common first names. |
| Surnames | Identifies common surnames. |
| Physician Names | Identifies physician names. |
Other Filters
The following non-person’s name filters are also available.
| Type | Description |
|---|---|
| Ages | Identifies ages such as 33.5 years old |
| Bank Routing Numbers | Identifies bank (ABA transit) routing numbers. |
| Bitcoin Addresses | Identifies Bitcoin addresses such as 127NVqnjf8gB9BFAW2dnQeM6wqmy1gbGtv |
| Cities | Identifies common cities |
| Counties | Identifies common counties |
| Countries | Identifies common countries |
| Credit Card Numbers | Identifies VISA, American Express, MasterCard, and Discover credit card numbers. |
| Currency | Identifies USD currency. |
| Dates | Identifies dates in many formats such as May 22, 1999 |
| Driver’s License Numbers | Identifies driver’s license numbers for all 50 US states |
| Email Addresses | Identifies email addresses |
| Hospitals and Hospital Abbreviations | Identifies common hospital names and their abbreviations |
| IBAN Codes | Identifies international bank account numbers |
| IP Addresses | Identifies IPv4 and IPv6 addresses |
| MAC Addresses | Identifies network MAC addresses |
| Passport Numbers | Identifies US passport numbers |
| Phone Numbers | Identifies phone numbers and phone number extensions |
| Sections | Identifies sections in text denoted by start and stop markers |
| SSNs and TINs | Identifies US SSNs and TINs |
| States and State Abbreviations | Identifies US state names and abbreviations |
| Tracking Numbers | Identifies UPS, FedEx, and USPS tracking numbers |
| URLs | Identifies URLs |
| VINs | Identifies vehicle identification numbers |
| Zip Codes | Identifies US zip codes |
Custom Filter Types of Sensitive Information
In addition to the predefined types of sensitive information listed in the table above, you can also define your own types of sensitive information. Through custom identifiers and dictionaries, Philter can identify many other types of information that may be sensitive in your use-case. For example, if you have patient identifiers that follow a pattern of AA-00000 you can define a custom identifier for this sensitive information.
Philter can be configured to look identify sensitive information based on custom dictionaries. When a term in the dictionary is found in the text, Philter will treat the term as sensitive information and apply the given replacement strategy.
Custom dictionaries support fuzziness to accommodate for misspellings. The replacement strategy for a custom dictionary has a sensitivityLevel that controls the amount of allowed fuzziness.
| Type | Description |
|---|---|
| Custom Dictionaries | Identifies sensitive information based on dictionary values. |
| Custom Identifiers | Identifies custom alphanumeric identifiers that may be used for medical record numbers, patient identifiers, account number, or other specific identifier. |
