Data Object Scope Control for Compliance Gap Remediation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computing systems face challenges in efficiently and flexibly managing controls across various data processes due to the complexity and scale of data assets and the need to comply with multiple system requirements frameworks, leading to potential non-compliance and inaccurate data handling.
Innovation Solution
A control management system that modifies data objects and associations within a digital data repository to adapt control scopes in response to changes, ensuring compliance with system requirements frameworks by merging, splitting, or cloning data objects, and preventing changes during active data analysis projects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computing systems implement multiple controls to comply with different system requirements frameworks, then compliance coverage is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal control management system that can manage multiple controls from different system requirements frameworks (PCI DSS, HIPAA, SOX, etc.) through a single unified interface. The system assigns unique identifiers to controls and uses a standardized data structure that can represent any control type, allowing one system to handle diverse compliance requirements without proportionally increasing complexity.
Solution Approach 2:
The patent employs a hierarchical control structure where controls are organized in nested levels of scope (entity-level, data process-level, and data asset-level). This nesting allows broader compliance frameworks to contain more specific controls, enabling the system to manage multiple frameworks simultaneously by leveraging the hierarchical relationships rather than treating each control independently.
2Adaptability or versatility
If the control scope is changed to adapt to regulatory changes, then adaptability is improved, but loss of time occurs due to system updates
Solution Approach 1:
The patent implements preliminary action by pre-defining control templates and data structures that can accommodate various system requirements frameworks. When new regulatory requirements arise, the system can quickly instantiate appropriate controls using pre-configured templates rather than building controls from scratch, significantly reducing the time needed to adapt to regulatory changes.
Solution Approach 2:
The patent employs dynamic control scope modification capabilities that allow the system to adjust control applicability in real-time based on changing regulatory requirements. The control management system can dynamically add, remove, or modify which data processes and data assets are subject to specific controls without requiring system-wide reconfiguration, enabling rapid adaptation while minimizing disruption.
3Reliability
If controls are implemented across large scale computing systems with multiple data assets, then compliance coverage is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements comprehensive feedback mechanisms that automatically monitor and report on control implementation status across the computing system. The system tracks evidence of control effectiveness, generates compliance reports, and provides real-time feedback on which controls are properly implemented and which require attention. This automated feedback loop simplifies operations by eliminating manual compliance tracking and allowing operators to focus on remediation rather than monitoring.
Solution Approach 2:
The patent enables self-service capabilities where the control management system automatically performs routine compliance management tasks such as generating compliance reports, tracking control evidence, and updating control status. The system can autonomously manage the compliance documentation and evidence collection processes, reducing the operational burden on personnel and making compliance management more straightforward even across large-scale systems.
Data Source
AI summary
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems according to detect and correct configuration gaps with specific system requirements frameworks. Specifically, the disclosed system accesses a digital data repository to determine attribute values of data objects representing functions or infrastructure associated with handling target data for an entity. The disclosed system determines a digital representation of a system requirements framework that indicates controls associated with handling specific data types. Based on the attribute values and a gap rules set associated with the system requirements framework, the disclosed system determines configuration gaps to be addressed via control actions for installing controls in connection with various data assets or data processes. The disclosed system generates tasks to display via a graphical user interface of a computing device for applying modifications to the data assets and/or data processes to address the configuration gaps.