Automated Personal Data Deletion Across Multiple Storage Systems
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Solution Overview
Problem
Current systems lack efficient methods for managing and deleting personal data across multiple storage locations within organizations, leading to compliance challenges with privacy and security policies.
Innovation Solution
A personal data processing and deletion system utilizing processors and computer memory to generate and populate data models, identifying storage locations of personal data, and automatically facilitating deletion upon request, ensuring compliance with legal and industry standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to locate and delete personal data across multiple storage locations, then deletion accuracy can be maintained, but the time and resources required increase significantly
Solution Approach 1:
The system enables self-service by automatically locating and deleting personal data without requiring manual intervention. The automated system scans storage locations, identifies personal data using defined criteria, and performs deletion operations autonomously, eliminating the time-consuming manual process while maintaining accuracy through systematic verification
Solution Approach 2:
The patent replaces manual mechanical search and deletion processes with an automated computer-based system. The system uses algorithms to scan storage locations, identify personal data patterns, and execute deletion commands, substituting human effort with automated computational processes that are both faster and equally accurate
2Reliability
If comprehensive scanning of all storage locations is performed to ensure complete deletion, then deletion completeness improves, but system complexity and processing time increase
Solution Approach 1:
The system divides the comprehensive scanning task into manageable segments by organizing storage locations into categories and using data models to represent different data types. This segmentation allows the system to methodically process each segment with appropriate deletion criteria, ensuring completeness without overwhelming system complexity
Solution Approach 2:
The patent introduces data models as intermediary structures that mediate between storage locations and deletion operations. These data models provide a standardized representation of personal data across different storage systems, enabling consistent identification and deletion while simplifying the overall system architecture
3Productivity
If automated deletion systems are implemented across multiple systems, then operational efficiency improves, but the risk of unauthorized access and data breaches increases
Solution Approach 1:
The system implements feedback mechanisms that log and track all deletion operations, providing audit trails for security monitoring. This feedback loop allows organizations to monitor automated deletion processes, detect potential unauthorized access, and maintain security oversight while benefiting from automated operational efficiency
Solution Approach 2:
The patent uses data models and standardized interfaces as intermediaries between the automated deletion system and various storage systems. This intermediary layer abstracts the complexity of different storage systems while maintaining consistent security protocols, enabling efficient automated deletion without directly exposing security vulnerabilities
Data Source
AI summary
In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization's systems, the system may: (1) automatically determine where the data subject's personal data is stored; and (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject's personal data from the various systems (e.g., by automatically assigning a plurality of tasks to delete data across multiple business systems to effectively delete the data subject's personal data from the systems).