Anonymity Measuring Device Using Conditional Entropy for Data Confidentiality
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Solution Overview
Problem
Current methods lack an effective way to determine when data has been sufficiently anonymized for transmission to third parties without compromising confidentiality, as existing systems are either too limited or inadequate in ensuring anonymity across all database entries.
Innovation Solution
A data anonymity measuring device calculates conditional entropy for each entry in the anonymized database based on the original database, comparing it to a threshold value to determine if the data can be safely transmitted, and includes a method to further anonymize or erase the data if it is not sufficiently anonymized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is anonymized to maintain confidentiality, then data security is improved, but it becomes difficult to determine when sufficient anonymization has been achieved
Solution Approach 1:
The patent replaces manual assessment of anonymization sufficiency with an automated information-theoretic measurement system. The calculation unit computes conditional entropy values for each database entry, substituting subjective evaluation with objective mathematical measurement to determine when anonymization is sufficient.
Solution Approach 2:
The patent introduces conditional entropy as an intermediary metric between the anonymized data and the original data. This intermediary measurement allows the system to quantify the information loss and determine anonymization sufficiency without directly exposing the original data or requiring manual assessment.
2Reliability
If comprehensive anonymization is applied to all database entries, then data security is improved, but data utility may be reduced
Solution Approach 1:
The patent applies local quality by evaluating and treating each database entry individually based on its specific anonymization characteristics. The calculation unit computes conditional entropy for each entry separately, allowing different entries to be assessed according to their individual information content and anonymization requirements, rather than applying uniform anonymization to all data.
Solution Approach 2:
The patent uses parameter changes by measuring the conditional entropy value for each database entry and using this parameter to determine whether the entry meets the sufficiency threshold. Entries with conditional entropy values meeting or exceeding the threshold are considered sufficiently anonymized, while those below the threshold require further anonymization or are excluded from transmission.
Data Source
AI summary
The invention concerns a data anonymity measuring device for selectively transmitting an anonymized database to a third party comprising: calculation means (402) coupled to at least one memory, the memory storing an original database (204) and said anonymized database (206), said calculation means arranged to calculate the conditional entropy for each entry in said anonymized database based on entries in said original database; comparing means (406) arranged to compare at least one of said conditional entropies with a threshold value; and output means (410) arranged to transmit said anonymized database based on the result of said comparison.