Privacy Consent Mapping for Sensitive Data Minimization

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing online services lack integration of privacy requirements, making it difficult to comply with regulations like privacy-by-default, which can hinder business operations and may not align with users' desires for data disclosure control.

Innovation Solution

A method and system that allow users to consent to relaxing default privacy policies for sensitive data fields, using a consent privacy rule to minimize and expand data visibility based on user authorization, integrating a minimization service to manage sensitive data access.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If privacy-by-default is implemented to protect personal information, then data protection is improved, but business operations are hindered due to restricted data access

Engineering Contradiction:
Improvedata protectionVSAvoidbusiness operations
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The system implements dynamic privacy control where the privacy level of data fields can be changed from default protected state to accessible state based on user consent. The mapping aspect dynamically adjusts data accessibility at runtime according to user preferences, allowing the system to transition between privacy protection and business operation modes as needed.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system changes the accessibility parameter of data fields from restricted (privacy-by-default) to permitted (privacy-by-consent) based on user input. The mapping aspect modifies the effective visibility parameter of sensitive fields according to the consent privacy rule, enabling flexible parameter adjustment between protection and access states.

Inventive Principle:
Principle #35Parameter changes

2Reliability

If privacy-by-default is applied to all data fields, then data protection is improved, but user flexibility in data disclosure is reduced

Engineering Contradiction:
Improvedata protectionVSAvoiduser flexibility
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system provides dynamic user control over privacy settings, allowing users to adjust their data disclosure preferences interactively. The mapping aspect responds to user consent decisions in real-time, dynamically modifying which fields are accessible and to what extent, thereby providing adaptability while maintaining protection by default.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system applies different privacy levels to different data fields based on user consent. Instead of uniform protection, the mapping aspect selectively applies accessibility to specific fields (e.g., name, email, location) depending on the user's consent privacy rule, allowing local customization of privacy properties for each field.

Inventive Principle:
Principle #3Local quality

3Ease of operation

If existing software infrastructure is used without privacy modifications, then ease of operation is maintained, but privacy compliance is worsened

Engineering Contradiction:
Improvesystem operationVSAvoidprivacy compliance
Core Design Contradiction:
Ease of operationVSReliability

Solution Approach 1:

The mapping aspect serves as an intermediary layer between the existing application code and the privacy enforcement mechanism. It intercepts data access operations and applies privacy rules without requiring modifications to the core application logic, allowing privacy compliance to be enforced while maintaining the original system's ease of operation through a separate enforcement layer.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments privacy enforcement from application development by introducing a separate mapping aspect that handles privacy compliance independently. This segmentation allows the existing application infrastructure to remain unchanged while privacy rules are applied through a distinct layer, maintaining operational simplicity while achieving compliance.

Inventive Principle:
Principle #1Segmentation

4Productivity

If full data accessibility is provided to meet business needs, then productivity is improved, but data protection is worsened

Engineering Contradiction:
Improvebusiness operationsVSAvoiddata protection
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The system provides selective data accessibility where different levels of protection are applied to different fields based on user consent. The mapping aspect allows certain fields to be fully accessible for business operations while maintaining protection for other fields, enabling local optimization of both productivity and data protection rather than uniform access or protection.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

Instead of full data accessibility, the system implements partial access controlled by the mapping aspect. It provides just enough data access as permitted by the consent privacy rule, avoiding excessive access while still enabling necessary business operations. The mapping aspect filters and controls the degree of data exposure to achieve minimal sufficient access for productivity.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS9443101B2Low-cost specification and enforcement of a privacy-by-consent-policy for online services
Publication Date: 2016.09.13 GENESEE VALLEY INNOVATIONS LLC
  • US9443101B2 patent drawing
  • US9443101B2 patent drawing
  • US9443101B2 patent drawing

AI summary

A system and method for implementing a privacy policy in an application to be run are provided. Definitions are received for a set of fields. At least one of the fields is designated as sensitive by a default privacy policy. A user is provided with a consent editor whereby the user can consent to relaxing the default privacy policy for at least one of the sensitive fields. A consent privacy rule is generated based on the received consent. A mapping aspect is provided which identifies joins at which code of the application is to be augmented by calling a minimization service to apply the default privacy policy by generating a minimized value of data in each of the designated sensitive fields used by the application unless there is a generated consent privacy rule which authorizes relaxation of the default privacy policy for the user's data in a respective sensitive field.