Automated Data Privacy Campaign Orphan Identification
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage personal data in compliance with privacy and security policies, particularly to identify and remove personal data not associated with active privacy campaigns, as frequent breaches and data misuse have increased, and individuals seek tools to minimize data processing by entities they do not actively engage with.
Innovation Solution
A computer-implemented data processing method that accesses and scans data assets to generate a catalog of privacy campaigns and personal information, identifies data not associated with these campaigns, and automatically removes or retains it based on user selection, ensuring compliance with privacy policies and minimizing data storage by non-active entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If personal data is retained in data assets for potential future use, then data availability for business operations is improved, but data security risk increases due to potential breaches and misuse
Solution Approach 1:
The system performs preliminary identification of data not associated with active privacy campaigns before actual removal occurs. By proactively scanning data assets, generating catalogs of privacy campaigns, and identifying orphaned personal data in advance, the system prepares for secure data minimization while maintaining compliance, thus reducing security risks before they can materialize into breaches
Solution Approach 2:
The system systematically discards personal data that is no longer associated with active privacy campaigns through automated removal processes. This principle enables the organization to eliminate unnecessary data holdings that pose security risks, while the cataloging and identification mechanisms ensure that only appropriate data is removed, preserving business-critical information
2Measurement precision
If manual processes are used to identify and manage personal data associated with privacy campaigns, then data accuracy is improved through human review, but productivity decreases due to time-consuming manual efforts
Solution Approach 1:
The system performs self-service by automatically scanning data assets, generating privacy campaign catalogs, identifying personal data not associated with active campaigns, and executing removal processes without requiring continuous human intervention. The automated workflow maintains accuracy through systematic comparison of data against campaign records while dramatically improving productivity by eliminating manual review bottlenecks
Solution Approach 2:
The system implements feedback mechanisms where the generated catalog of privacy campaigns and associated personal data is continuously compared against current data assets. This feedback loop ensures accurate identification of orphaned data by constantly verifying data-campaign associations, maintaining measurement precision while enabling high-speed automated processing
3Manufacturing precision
If comprehensive data scanning and cataloging is performed to identify all personal data, then compliance accuracy is improved, but device complexity increases due to extensive processing requirements
Solution Approach 1:
The system segments the comprehensive data management task into distinct modular components: (1) scanning data assets to identify personal data, (2) generating a catalog of privacy campaigns and associated data, (3) comparing catalog data against current data assets, (4) identifying orphaned personal data, and (5) executing removal processes. This segmentation maintains compliance accuracy through thorough processing while reducing perceived complexity by organizing operations into manageable, independent stages
4Loss of information
If personal data not associated with active privacy campaigns is retained, then data utility for potential future campaigns is improved, but loss of information increases due to potential data breaches and misuse
Solution Approach 1:
The system performs preliminary identification and removal of orphaned personal data before any potential security incidents can occur. By proactively eliminating data not associated with active privacy campaigns, the system prevents future data breaches and misuse while the cataloging mechanism ensures that data useful for future campaigns can be quickly re-associated and retained when needed
Solution Approach 2:
The system discards orphaned personal data through automated removal processes while maintaining the capability to recover and re-use data for future privacy campaigns. The catalog of privacy campaigns and associated personal data serves as a repository that enables quick re-association of data when new campaigns are initiated, thus eliminating data breach risks from orphaned data while preserving data utility for legitimate future uses
Data Source
AI summary
In particular embodiments, a Data Transfer Risk Identification System may be configured to analyze one or more data systems (e.g., data assets), identify data transfers between/among those systems, apply data transfer rules to each data transfer record, perform a data transfer assessment on each data transfer record based on the data transfer rules to be applied to each data transfer record, and calculate a risk score for the data transfer based at least in part on the one or more data transfer risks associated with the data transfer record.