Privacy Campaign Data Records for Sensitive Data Reconciliation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Organizations face challenges in identifying and representing data flows of personal data through complex data networks, making it difficult to implement appropriate data controls and ensure compliance with privacy regulations.
Innovation Solution
A method and system that reconcile sensitive data with existing data flows by identifying matching data, updating the data flow to include unrepresented data, and defining privacy-related attributes, facilitating network operations and risk assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations implement comprehensive data controls to ensure privacy compliance, then privacy protection is improved, but system complexity increases
Solution Approach 1:
The patent introduces a privacy campaign data record as an intermediary structure that mediates between raw sensitive data and data flow representations. This record contains privacy-related attributes (data subject, purpose, legal basis, retention period) that serve as a bridge to map personal data to specific data flows, enabling comprehensive privacy controls without directly complicating the entire data processing system.
Solution Approach 2:
The patent segments privacy management into discrete privacy campaigns, each associated with specific sensitive data and privacy-related attributes. By dividing the overall privacy compliance task into separate campaign records, the system can manage complexity through modular organization rather than attempting to control all data processing activities as a single monolithic system.
2Measurement precision
If organizations maintain detailed data maps and privacy campaign records, then data flow representation accuracy is improved, but data processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-establishing privacy campaign data records with privacy-related attributes before data processing occurs. These records are prepared in advance with all necessary privacy information (data subject, purpose, legal basis, retention period), so that when data flows need to be represented or processed, the privacy context is already available without requiring real-time analysis or additional processing time.
Solution Approach 2:
The patent creates a copy of privacy information in the privacy campaign data record structure, which contains replicated privacy-related attributes. This copying approach allows the system to reference privacy information multiple times without re-processing or re-analyzing the original data, thereby maintaining accurate data flow representation while avoiding time-consuming repeated operations.
3Measurement precision
If organizations reconcile sensitive data with data flows by updating data flow records, then data accuracy is improved, but system operations become more complex
Solution Approach 1:
The patent merges the privacy data representation function with the existing data flow record structure. By combining privacy-related attributes (data subject, purpose, legal basis, retention period) directly into the data flow record, the system achieves accurate data representation without creating separate complex reconciliation processes. The privacy information and data flow information are unified in a single record structure.
Solution Approach 2:
The patent makes the data flow record universal by enabling it to serve multiple functions: representing data flow paths, storing privacy-related attributes, and providing the basis for both privacy compliance and data loss prevention. This multi-functionality eliminates the need for separate specialized records for each function, thereby reducing operational complexity while maintaining data accuracy.
Data Source
AI summary
Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.