Philter identifies and removes sensitive information, such as Personally Identifiable Information (PII) and Protected Health Information (PHI), from natural language text.
Philter was designed to be integrated into virtually any existing system and be usable from big-data applications Apache NiFi, Apache Kafka, and AWS Kinesis.
Capabilities of Philter
- Philter uses state-of-the-art natural language processing (NLP) and trained neural networks to identify sensitive information such as PII and PHI in text.
- Philter can replace sensitive information with similar but random values. With consistent anonymization, documents can remain useful for secondary purposes by not losing meaning.
- Customizable filter profiles give full control over how sensitive information is identified and manipulated.
- Supports logic to manipulate sensitive information based on conditions such as zip code population and textual content.
- Can optionally store locations of sensitive information in text to a database for future reference.
Philter is available in two editions. The primary difference in the two editions is that the Enterprise edition includes support for usage of Philter with streaming applications.
|Standard Edition||Enterprise Edition|
|Customizable PHI and PII Filtering||Yes||Yes|
|Anonymization via Random Value Replacement||Yes||Yes|
|Works with Philter Studio||Yes - includes 5 licenses||Yes - includes 25 licenses|
|Works with Filter Profile Registry||Yes||Yes|
|Interoperability with Big-Data Applications||Yes||Yes|
|Support||Standard Email Support||Priority Email Support|
|Cost||Starts at $0.79 / hour |
Billed through your cloud platform
The blog posts and articles linked below provide example solutions using Philter to find and remove PII and PHI.
- Using AWS Kinesis Firehose Transformations To Filter Sensitive Information from Streaming Text
- Using Philter with Apache NiFi for Data Flow PHI Filtering