Graph Taxonomy Attributes for Cross-Domain Risk Aggregation
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Solution Overview
Problem
Conventional systems lack the ability to effectively manage computing environments across different domains handling specific data types, leading to disjointed management and increased risk of data breaches due to siloed access controls and lack of communication between domains.
Innovation Solution
A digital taxonomy library system that generates and modifies interactive graph-based taxonomies to represent relationships between nodes and attributes, allowing for dynamic management and aggregation of attribute values across domains, providing real-time notifications and automatic implementation of controls to mitigate risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional account management and mitigation practices are used to limit access to data, then data breach risks are reduced within specific domains, but the ability to assess compliance and determine relationships across different domains is lost
Solution Approach 1:
The system segments the computing environment into multiple domains, each with its own access controls and compliance requirements. By dividing the system into domain-specific units, it maintains granular security controls while enabling cross-domain relationship tracking through the graph-based taxonomy that connects nodes across domains.
Solution Approach 2:
The graph-based taxonomy system acts as an intermediary layer between domain-specific access controls and enterprise-wide compliance assessment. It captures and represents relationships across domains without requiring direct access to domain-specific data, enabling centralized visibility while preserving domain autonomy.
2Reliability
If access controls are implemented at the domain level, then security within each domain is improved, but communication and reporting between domains are limited
Solution Approach 1:
The graph-based taxonomy provides a universal framework that works across all domains simultaneously. It performs multiple functions: maintaining domain-specific security boundaries while enabling cross-domain relationship tracking, compliance assessment, and reporting through a single unified system.
Solution Approach 2:
The taxonomy system serves as an intermediary that enables cross-domain communication without requiring direct integration between domains. It captures relationships between nodes across domains and provides reporting capabilities while preserving domain-level security boundaries.
3Loss of information
If a centralized system is used to manage data across all domains, then cross-domain visibility is improved, but the complexity of managing diverse domain-specific controls increases
Solution Approach 1:
The system segments the management complexity by organizing nodes into domain-specific groups while maintaining a unified graph structure. This allows centralized visibility through the graph-based taxonomy while managing diversity through domain-oriented segmentation that simplifies control implementation.
Solution Approach 2:
The system creates a virtual representation (copy) of domain relationships through the graph-based taxonomy without requiring direct access to or management of actual domain-specific data and controls. This copying approach enables cross-domain visibility while avoiding the complexity of managing diverse domain implementations directly.
4Reliability
If domain-specific access controls are implemented, then data protection within domains is improved, but the ability to assess entity-wide risks is reduced
Solution Approach 1:
The graph-based taxonomy acts as an intermediary that captures domain-specific security attributes and relationships without requiring direct access to protected data. It enables entity-wide risk assessment by aggregating and analyzing relationship information across domains while preserving domain-level data protection boundaries.
Solution Approach 2:
The system creates a virtual model of the computing environment that copies relationship structures and security attributes across domains. This copied representation enables entity-wide risk assessment through analysis of the graph taxonomy without compromising actual data protection implemented at the domain level.
Data Source
AI summary
Methods, systems, and non-transitory computer readable storage media are disclosed for dynamically generating and modifying interactive graph-based taxonomies associated with data processes in various domains. The disclosed system generates node data objects representing a domain-category hierarchy in connection with one or more computing data processes via a library of tools. The disclosed systems generates an attribute data object corresponding to an attribute assigned to a node data object in the graph-based taxonomy and links the attribute data object to node data objects according to parent/child relationships of the hierarchy. The disclosed system utilizes the parent/child relationships of the node data objects and attribute data object to aggregate attribute values of the attributes according to one or more aggregation operations. The disclosed systems provide indications of the aggregated attribute values for display via a graphical user interface for use in performing data processes.