Filters
Describes the types of filters available in Philter.
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.
Philter can identify many predefined types of sensitive information. Each type, or filter, can be enabled or disabled separately from the other types in a filter profile.
Philter uses several methods to identify person's names.
Type | Description |
|---|---|
Identifies common first names | |
Identifies common surnames | |
Identifies full names using natural language processing analysis |
Type | Description |
|---|---|
Identifies ages such as 3.5 years old | |
Identifies Bitcoin addresses such as 127NVqnjf8gB9BFAW2dnQeM6wqmy1gbGtv | |
Identifies common cities | |
Identifies common counties | |
Identifies VISA, American Express, MasterCard, and Discover credit card numbers. | |
Identifies dates in many formats such as May 22, 1999 | |
Identifies driver's license numbers for all 50 US states | |
Identifies email addresses | |
Identifies common hospital names and their abbreviations | |
Identifies international bank account numbers | |
Identifies IPv4 and IPv6 addresses | |
Identifies network MAC addresses | |
Identifies US passport numbers | |
Identifies phone numbers and phone number extensions | |
Identifies sections in text denoted by | |
Identifies US SSNs and TINs | |
Identifies US state names and abbreviations | |
Identifies UPS, FedEx, and USPS tracking numbers | |
Identifies URLs | |
Identifies vehicle identification numbers | |
Identifies US zip codes |
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 |
|---|---|
Identifies sensitive information based on dictionary values. | |
Identifies custom alphanumeric identifiers that may be used for medical record numbers, patient identifiers, account number, or other specific identifier. |
Last modified 4mo ago