Privacy Markup on Entity Models for Data Protection
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Solution Overview
Problem
The increasing sophistication of identity theft and exponential attempts to obtain personal or sensitive information necessitate enhanced protection of digital data, particularly in systems where users may unknowingly input sensitive information that becomes identifiable when combined with other data.
Innovation Solution
A method to identify entries in an entity model as potentially private and sensitive, using boolean attributes to indicate whether an entry is personally identifiable and sensitive, with default settings and permission-based modification, applicable to relational databases, XML schemas, and object models, including CRM systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users input data without awareness of sensitivity, then data entry efficiency is improved, but data security and privacy protection deteriorate
Solution Approach 1:
The system performs preliminary classification of data fields during entity model definition, marking fields as potentially personally identifiable or potentially sensitive before data entry occurs. This advance preparation allows automatic privacy marking during data entry without requiring user awareness or manual intervention at entry time, thus maintaining efficiency while improving security.
2Measurement precision
If combination of multiple data entries is analyzed for privacy, then privacy detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments privacy detection into two distinct phases: (1) field-level marking during entity model definition where individual fields are marked as potentially personally identifiable or potentially sensitive, and (2) record-level assessment during data entry where the combination of marked fields is evaluated. This segmentation reduces system complexity by handling privacy concerns at appropriate granularities rather than analyzing all possible combinations simultaneously.
3Object-affected harmful factors
If default privacy marking is applied to all entries, then data protection is improved, but ease of operation deteriorates
Solution Approach 1:
The system applies privacy marking selectively rather than uniformly. During entity model definition, individual fields are marked as potentially personally identifiable or potentially sensitive based on their specific characteristics. During data entry, records receive privacy marking only when they contain combinations of marked fields. This localized approach provides protection where needed while avoiding unnecessary complexity for non-sensitive data, improving ease of operation.
Data Source
AI summary
A method of identifying an entry in an entity model as being at least one of potentially private and potentially sensitive is disclosed. The method may include creating an indication related to a specific entry that indicates whether the specific entry is one of potentially personally identifiable and potentially sensitive or both and allowing the indication to be modified to indicate whether the specific entry is one of potentially personally identifiable and potentially sensitive or both.