Selective Data Anonymization via Token Replacement
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Solution Overview
Problem
Third-party network services face challenges in anonymizing data items subject to privacy or confidentiality restrictions, such as ePHI or PII, as simple deletion can cause inconsistencies within larger data sets, making it difficult to maintain compliance with regulations.
Innovation Solution
A network computer system that selectively anonymizes data items by identifying those meeting specific conditions, replacing them with uniquely generated tokens, and storing the anonymized data within a third-party network service, maintaining the data structure and utility while ensuring compliance with privacy regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simple deletion of specific data items is performed, then privacy compliance is improved, but data set consistency deteriorates
Solution Approach 1:
The patent extracts sensitive data items from the data set and replaces them with anonymized tokens. This removes the harmful element (PII/ePHI) while preserving the structural integrity of the remaining data, thus achieving both privacy compliance and data consistency.
Solution Approach 2:
The patent changes the parameter of sensitive data by transforming it into an anonymized form through tokenization. The original data is replaced with a token that preserves referential integrity without containing the actual sensitive information, resolving the contradiction between deletion and consistency.
2Reliability
If sensitive data items are anonymized and replaced with tokens, then privacy compliance is improved, but device complexity increases
Solution Approach 1:
The patent introduces a token as an intermediary element between the original sensitive data and the anonymized representation. This token serves as a mediator that maintains referential integrity while eliminating the need to store or process actual sensitive information, achieving privacy compliance without excessive complexity.
Solution Approach 2:
The patent creates a simplified copy of the sensitive data in the form of an anonymized token. This token copy preserves the structural and relational properties of the original data without containing the actual sensitive information, reducing complexity while maintaining compliance.
3Adaptability or versatility
If data items are anonymized while maintaining data structure, then data utility is improved, but processing complexity increases
Solution Approach 1:
The patent changes the parameter of selected data items by replacing them with tokens that match the expected data format. This allows the anonymized data to maintain its structural properties and utility while being processed through existing data pipelines with minimal additional complexity.
Data Source
AI summary
A data anonymization computer system selectively anonymizes data items from data structures prior to forwarding the data structures to a third-party network service. The data anonymization computer system identifies at least a respective data item of the data structure that meets a set of conditions, including at least a first condition in which at least a portion of the respective data item has a format that coincides with the predetermined format and replaces a set of characters of the respective data item having the format with a string of characters of a respective token of a pool of tokens. The data anonymization computer system forwards the data structures to the third-party network service with each of the respective data items having the string of characters of the respective token in place of the replaced set of characters.