Asset Relationship Mapping for Risk Propagation Path Analysis
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Solution Overview
Problem
Existing network discovery systems lack efficient methods for dynamic asset relationship mapping and risk propagation analysis, leading to suboptimal cybersecurity risk management due to static categorization of assets and connections.
Innovation Solution
A system that computes the extent of traversal from a target asset to other assets in a network for risk propagation analysis, using asset graphs to determine connections based on risk event severity, asset importance, and security profiles, and generates tailored recommendations for risk mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static categorization of assets and connections is used, then device complexity is reduced, but risk analysis precision deteriorates
Solution Approach 1:
The patent implements dynamic asset relationship mapping that updates connection relationships based on real-time network activity and risk event propagation. The system transitions from static categorization to dynamic relationship tracking, where connection degrees are continuously updated based on actual network behavior and risk propagation patterns, enabling precise risk analysis without requiring overly complex fixed structures
Solution Approach 2:
The patent segments the network into multiple connection degrees (first-degree connections, second-degree connections, etc.) based on the number of hops from a target asset. This segmentation allows the system to analyze risk propagation at different levels of the network hierarchy, providing precise risk analysis by examining connections at specific distances while maintaining manageable complexity through structured organization
2Measurement precision
If comprehensive network mapping is performed, then risk propagation analysis accuracy is improved, but computational resources consumed increase
Solution Approach 1:
The patent applies partial action by analyzing only the necessary connection degrees based on risk event characteristics. Instead of comprehensively mapping the entire network, the system determines the number of connections to traverse based on risk severity and asset importance, performing risk propagation analysis only to the extent required by the specific risk event, thereby reducing computational resource consumption while maintaining adequate accuracy
Solution Approach 2:
The patent dynamically adjusts analysis parameters based on risk event severity and asset importance. The system modifies the number of connection degrees to traverse and the depth of risk propagation analysis according to the specific characteristics of each risk event, optimizing computational resource allocation by performing more extensive analysis only when necessary and reducing analysis scope for lower-risk scenarios
3Measurement precision
If dynamic relationship mapping is implemented, then risk propagation analysis accuracy is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic relationship mapping that updates connection relationships based on real-time network activity and risk event propagation. The system maintains a dynamic model of network relationships that can adapt to changing network conditions, enabling accurate risk propagation analysis while managing complexity through automated updates and real-time adjustments
Solution Approach 2:
The system incorporates feedback mechanisms where risk propagation analysis results feed back into the relationship mapping process. Connection degrees and relationship weights are adjusted based on observed risk propagation patterns and analysis outcomes, creating a self-adjusting system that improves accuracy over time while managing complexity through automated feedback loops
Data Source
AI summary
A system generates a graph of assets in a network. The system defines connections between assets within the graph. The system identifies a risk event with an associated risk severity. The system determines a number of connections to traverse for generating a risk analysis pathway through the graph of assets in the network based on the associated risk severity associated with the risk event. The system generates a recommendation to address the identified risk.