Adjacency Matrix for Network Security Risk Scoring
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Solution Overview
Problem
Current information sharing systems and network security measures lack effective methods to identify and mitigate network security risks associated with access privileges and organizational hierarchies, leading to potential vulnerabilities that can be exploited by attackers.
Innovation Solution
A method that uses data extraction, matrix processing, and analytic techniques to generate an adjacency matrix representing connections between individuals, groups, and access privileges, allowing for the calculation of risk scores and automatic application of security controls to mitigate identified security risks by collapsing data structures and applying appropriate security measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If access privilege data and organizational hierarchy data are stored in detailed adjacency matrices, then security risk analysis precision is improved, but data storage demands increase
Solution Approach 1:
The patent combines access privilege data and organizational hierarchy data into a unified adjacency matrix structure that represents both types of relationships simultaneously. This merging allows the system to analyze security risks across multiple dimensions (individuals, groups, access privileges) without requiring separate storage structures, thus maintaining analysis precision while optimizing storage efficiency.
Solution Approach 2:
The system dynamically adjusts the granularity and detail level of the adjacency matrix based on analysis needs. By changing parameters such as which nodes (individuals, groups, privileges) are included and how relationships are weighted, the system can optimize between storage efficiency and analysis precision for different security assessment scenarios.
2Measurement precision
If comprehensive access privilege data is collected and analyzed, then security risk identification accuracy is improved, but system complexity increases
Solution Approach 1:
The adjacency matrix serves as an intermediary data structure that simplifies the complex relationships between individuals, groups, and access privileges. By representing all relationships in a standardized matrix format with clear indexing and scoring mechanisms, the system reduces the complexity of analyzing comprehensive security data while maintaining high identification accuracy.
Solution Approach 2:
The adjacency matrix structure is designed to be universal, handling multiple types of relationships (individual-individual, individual-group, individual-privilege) through a single data structure. This multi-functionality reduces system complexity by eliminating the need for separate data structures for different relationship types, while still enabling comprehensive security risk analysis.
3Manufacturing precision
If detailed connections between individuals and access privileges are maintained, then security control precision is improved, but data processing time increases
Solution Approach 1:
The system pre-calculates and stores access privilege scores and risk metrics in the adjacency matrix structure before security incidents occur. By performing preliminary analysis and storing intermediate results (such as privilege scores, group criticality scores) in the matrix, the system reduces processing time during actual security control operations while maintaining precise control capabilities.
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying network security risks. One of the methods includes receiving organizational hierarchy data and receiving access privilege data for a network, generating an adjacency matrix that represents connections between individuals within the organizational hierarchy and various groups, and that represents connections between the individuals and various access privileges, selecting an analytic technique for analyzing the adjacency matrix, determining, for each individual, an individual score that represents a security risk associated with the individual's network account, and in response to determining that the individual score meets a threshold, applying security controls.