Progressive Mapping Domains for Time-Based Data Anonymization
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Solution Overview
Problem
Existing anonymization methods require all data to be collected before anonymization can be applied, leading to prolonged unusability of the data for secondary purposes.
Innovation Solution
A method and device for anonymizing data using generalization, allowing anonymization of initial data records with a first set of mapping ranges, and subsequent data records with increasingly more comprehensive mapping ranges, ensuring k-anonymity and l-diversity without waiting for complete data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If anonymization is performed only after complete data collection, then data anonymity is ensured, but data usability for secondary purposes is prolongedly restricted
Solution Approach 1:
The patent applies preliminary action by performing anonymization on data subsets before complete data collection is finished. The system identifies anonymizable subsets of data, applies anonymization techniques to them, and makes them usable for secondary purposes in advance, rather than waiting for the entire dataset to be collected and anonymized all at once.
Solution Approach 2:
The patent segments the complete dataset into multiple subsets that can be independently anonymized. By dividing the data into manageable portions and processing them separately, the system enables incremental anonymization and release of data for secondary purposes while maintaining anonymity guarantees for each segment.
2Productivity
If anonymization is performed incrementally as data is collected, then data usability is improved, but ensuring consistent anonymity across all data becomes more complex
Solution Approach 1:
The system performs preliminary identification of anonymizable data subsets and pre-computes anonymization parameters before actual anonymization execution. This preliminary preparation simplifies the subsequent anonymization process and ensures consistency across incremental processing stages.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors the anonymization status of data subsets, adjusts anonymization parameters based on accumulated data characteristics, and ensures consistency across different time points. The feedback loop maintains anonymity guarantees while adapting to evolving data patterns.
Data Source
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AI summary
The present invention relates to a computer-implemented method for anonymizing data by means of generalization, wherein the data at a first time comprises a first set of first data records and at a second time comprises a second set of second data records. The first data records are a subset of the second data records. The method comprises generating (1102) a first generalization for the first data records that satisfies a required anonymization, wherein the first generalization comprises a first set of mapping domains with which values of a quasi-identifier of the data are generalized, and generating (1104) a second generalization for the second data records that satisfies the required anonymization, wherein the second generalization comprises a second set of mapping domains with which values of the quasi-identifier are generalized.The second group includes more assignment areas than the first group.