Version-Specific Data Anonymization Dictionaries for Software Applications
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Solution Overview
Problem
Existing data anonymization schemes fail to ensure that all sensitive fields are properly anonymized across different versions of software applications, leading to potential data leaks, as they often apply universal anonymization methods that may not account for version-specific data structures and requirements.
Innovation Solution
The development of version-specific data anonymization dictionaries that are validated against database service tables to ensure comprehensive anonymization, with each software version having its own dictionary, and the use of machine learning algorithms like BERT for generating dictionaries that accurately identify and anonymize sensitive data fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a universal anonymization scheme is applied to all software versions, then the implementation complexity is reduced, but the reliability of data protection deteriorates because version-specific data structures may not be properly anonymized
Solution Approach 1:
The patent segments the anonymization process by creating separate anonymization dictionaries for each software version. Each dictionary is tailored to the specific data structures and fields present in that version, ensuring comprehensive coverage. This segmentation resolves the contradiction by maintaining low implementation complexity through a standardized dictionary-based approach while achieving high reliability through version-specific customization.
Solution Approach 2:
The patent applies local quality by making each anonymization dictionary version-specific rather than using a universal scheme. Each dictionary contains anonymization rules customized to the particular data structures, fields, and sensitivity requirements of its corresponding software version. This allows the system to maintain simplicity in the overall architecture while achieving high reliability through localized, version-appropriate anonymization strategies.
2Reliability
If version-specific anonymization dictionaries are created for each software version, then the reliability of data anonymization is improved, but the device complexity increases due to maintaining multiple dictionaries
Solution Approach 1:
The patent applies universality by creating a centralized anonymization dictionary repository that serves all software versions. The system universally manages multiple version-specific dictionaries through a single interface, allowing developers to retrieve the appropriate dictionary based on the software version being tested. This resolves the complexity issue by providing a universal access mechanism while maintaining version-specific reliability.
Solution Approach 2:
The patent introduces an intermediary component - the anonymization dictionary repository - that mediates between the multiple version-specific dictionaries and the data anonymization process. This intermediary automatically selects and provides the correct dictionary for each software version, eliminating the need for manual dictionary management and reducing overall system complexity while maintaining high reliability through accurate version matching.
3Productivity
If user data is transferred to developers for testing, then the productivity of product improvement is enhanced, but the risk of data leakage increases due to potential exposure of sensitive information
Solution Approach 1:
The patent applies preliminary action by performing data anonymization before transferring user data to developers for testing. The system automatically identifies the software version, selects the appropriate anonymization dictionary, and applies the necessary anonymization transformations to remove or mask sensitive information. This preliminary anonymization action enables productive testing while eliminating data leakage risks, as developers receive already-anonymized data that cannot be used to identify users.
Data Source
AI summary
A system may store user data associated with a usage of a software application. A system may receive a request for the user data from a developer of the software application. A system may determine whether the user data is generated from a first version of the software application or a second version of the software application. A system may in response to determining that the user data is generated from the first version of the software application, retrieving a first dictionary that indicates an anonymization scheme for transmitting the user data of the first version of the software application, wherein each version of the software application has a different dictionary. A system may execute the anonymization scheme on the user data to generate anonymized user data. A system may transmit the anonymized user data to the developer in response to the request.