Cardinal Node Prioritization in Knowledge Graphs
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Solution Overview
Problem
Existing systems lack an effective method to identify and prioritize nodes that significantly impact high-value target nodes, leading to inefficiencies in improving system vulnerabilities and cybersecurity risks.
Innovation Solution
A knowledge graph system that determines cardinal nodes by calculating their impact on target nodes using measures of hardness and centrality, prioritizing them for improvement to reduce overall vulnerability and cybersecurity risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all nodes in the knowledge graph are improved to reduce system vulnerabilities, then the overall system security is improved, but the time and resources required increase significantly
Solution Approach 1:
The patent extracts and identifies a small subset of critical nodes (cardinal nodes) from the entire knowledge graph that have the most significant impact on target nodes. By focusing only on these extracted cardinal nodes rather than all nodes, the system achieves effective security improvement with reduced time and resource investment. The cardinality score calculation identifies nodes that, when improved, provide the greatest reduction in overall system vulnerability.
Solution Approach 2:
The patent applies local quality by assigning different importance levels to different nodes based on their cardinality scores. Instead of treating all nodes uniformly, the system identifies specific locations (nodes) in the knowledge graph that require priority improvement. This localized approach allows resources to be concentrated on the most critical nodes rather than being distributed evenly across all nodes, thereby improving efficiency while maintaining system security.
2Measurement precision
If the knowledge graph includes all possible pathways and relationships, then the analysis comprehensiveness is improved, but the complexity of determining node priorities increases
Solution Approach 1:
The patent introduces a cardinality score parameter that combines multiple factors (centrality measures, hardness measures, pathway information) into a single prioritization metric. By changing the parameter representation from multiple separate considerations to a unified cardinality score, the system maintains comprehensive analysis of all pathways and relationships while simplifying the complexity of determining node priorities. The cardinality score serves as a consolidated measure that captures the essential information needed for prioritization.
3Object-affected harmful factors
If security measures are applied to all computing devices, then the cybersecurity risk is reduced, but the cost and operational disruption increase
Solution Approach 1:
The patent extracts a prioritized list of cardinal nodes from the complete knowledge graph, identifying the specific subset of computing devices that require immediate security attention. By applying security measures only to these extracted cardinal nodes rather than all devices in the network, the system achieves significant cybersecurity risk reduction while minimizing cost and operational disruption. The extraction process identifies the most critical vulnerability points that, when addressed, provide the greatest risk mitigation.
Solution Approach 2:
The patent implements partial action by applying security measures to only the necessary portion of the system (cardinal nodes) rather than the entire system. This partial approach is sufficient to achieve the primary goal of reducing cybersecurity risk to an acceptable level, while avoiding the excessive cost and operational disruption that would result from securing all computing devices uniformly. The cardinality-based prioritization ensures that the partial action taken is the most effective portion to address.
Data Source
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AI summary
This document describes knowledge graph systems that determine cardinal nodes in a knowledge graph that provide the most impact on target nodes of a system and improves the system by adjusting the impact of the actual elements represented by the cardinal nodes. In one aspect, a method includes obtaining a knowledge graph that represents a given system and that includes multiple nodes that each represent an element of the given system. One or more target nodes are identified in the knowledge graph based on a value parameter for each node in the knowledge graph. A cardinal value that represents an impact that the node has on the one or more target nodes is determined for each node in the knowledge graph. A priority order of the nodes is determined for improvement based on the cardinal values. Data indicating one or more of the nodes is provided based on the order.