Privacy Firewall Data Segmentation and Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for accessing private data fail to effectively protect privacy while making the information useful, as they often anonymize data to the point of losing its utility or risk breaching privacy.
Innovation Solution
A system and method that analyze private electronic data to identify non-private information, extract and tag it for use outside a privacy firewall, ensuring that only non-private elements are shared, thereby preserving privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is anonymized to protect privacy, then privacy protection is improved, but data utility deteriorates
Solution Approach 1:
The system segments data into distinct categories (private information, non-private information, and private data without non-private elements) and applies different handling rules to each segment. This allows selective sharing of non-private portions while preserving privacy-protected portions, resolving the contradiction between privacy protection and data utility.
Solution Approach 2:
Different portions of the data are treated with different levels of privacy protection based on their local characteristics. Non-private information is shared freely, while private information receives privacy protection. This local differentiation enables the system to maximize data utility where appropriate while maintaining privacy where necessary.
2Reliability
If data is anonymized to protect privacy, then privacy protection is improved, but the data becomes unusable
Solution Approach 1:
By segmenting data into usable non-private portions and privacy-protected portions, the system enables data to remain useful for analysis and processing while maintaining privacy protection. The non-private segments can be freely utilized without compromising the privacy of private segments.
Solution Approach 2:
The system extracts and separates non-private elements from private data, allowing these extracted elements to be used independently for various purposes while the original private data remains protected. This extraction process maintains both privacy protection and data usability.
3Loss of information
If all data is made accessible, then data utility is improved, but privacy protection deteriorates
Solution Approach 1:
The system divides data into accessible non-private portions and protected private portions, enabling broad data accessibility where appropriate while maintaining privacy protection where necessary. This segmentation prevents the need to choose between complete accessibility and complete protection.
Solution Approach 2:
Different accessibility levels are applied to different data portions based on their privacy characteristics. Non-private data is fully accessible, while private data receives restricted access. This local quality differentiation resolves the contradiction between overall data accessibility and privacy protection.
Data Source
AI summary
Systems and methods for protecting private data behind a privacy firewall are disclosed. A system for implementing a privacy firewall to determine and provide non-private information from private electronic data includes a data storage repository, a processing device, and a non-transitory, processor-readable storage medium. The storage medium includes programming instructions that, when executed, cause the processing device to analyze a corpus of private electronic data to identify a first one or more portions of the data having non-private information and a second one or more portions of the data having private information, tag the first one or more portions of the data as allowed for use, determine whether the second one or more portions of the data includes non-private elements, and if the second one or more portions of the data comprises non-private elements, extract the non-private elements and tag the non-private elements as information allowed for use.