Permission-Based Consumer Data Filtering With PII Anonymization
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Solution Overview
Problem
The escalation of security breaches involving personally identifiable information (PII) poses significant risks to individuals and organizations, leading to identity theft, legal liabilities, and loss of public trust, while existing systems lack effective methods for controlling data sharing and protecting PII.
Innovation Solution
A data management system (DMS) that stores PII data and allows owners to define data sharing permissions, converting PII into de-identified data and using pseudonyms or codes to maintain control over data dissemination, while enabling secure and controlled access for analysis and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If PII data is stored and shared for organizational purposes, then data utility and analytics capability are improved, but security risk and vulnerability to breaches increase
Solution Approach 1:
The patent extracts PII from the shared data by identifying and removing personally identifiable information fields before sharing data with third parties. This allows organizations to share valuable data for analytics and productivity while eliminating the security risks associated with PII exposure.
Solution Approach 2:
The patent introduces an intermediary data processing system that acts as a mediator between data storage and data sharing. This intermediary layer automatically filters and anonymizes data, enabling secure data utilization without direct exposure of sensitive information.
2Reliability
If PII data is filtered and anonymized to protect privacy, then security and privacy protection are improved, but data completeness and analytical value deteriorate
Solution Approach 1:
The patent applies local quality by selectively filtering only the PII portions of data while preserving the non-identifiable portions. This targeted approach maintains data completeness for analytical purposes while protecting privacy by removing only the necessary identifying fields.
Solution Approach 2:
The patent implements partial action by removing only the specific PII elements needed for privacy protection rather than anonymizing entire datasets. This selective filtering preserves sufficient data detail for meaningful analytics while achieving adequate privacy protection.
3Reliability
If data sharing permissions are strictly enforced to control access, then security control and compliance are improved, but data accessibility and collaboration efficiency worsen
Solution Approach 1:
The patent implements self-service by automatically enforcing data sharing permissions through automated filtering and anonymization systems. This eliminates the need for manual permission management while maintaining strict compliance, allowing seamless data accessibility without sacrificing security controls.
Solution Approach 2:
The patent applies preliminary action by pre-configuring data sharing permissions and automatically applying filters before data is shared. This proactive approach ensures compliance is built into the data sharing process from the start, eliminating barriers to collaboration while maintaining security requirements.
Data Source
AI summary
A system may include an interface configured to couple to a network, and includes a processor and a memory accessible to the processor. The memory may be configured to store instructions that, when executed, cause the processor to process search results corresponding to multiple data owners to selectively filter personally identifiable information (PII) associated with one or more consumers from the set of search results according to data sharing permissions for each of the data owners to produce filtered results. The instructions may further cause the processor to provide the filtered results to a user device through the network.