Automated Entity Relationship Analysis via Log Data Standardization
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Solution Overview
Problem
Conventional approaches for identifying relationships between entities are prone to errors due to the manual organization and analysis of vast amounts of data, which can lead to insufficient determination of relationships between entities.
Innovation Solution
A system configured to process and analyze log data from computing systems to identify relationships between login-based accounts by standardizing and enriching log data with geolocation information and whitelisting, and associating accounts accessed from the same network-based address for further review.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual organization and analysis of vast amounts of data is performed, then relationships between entities can be identified, but errors increase and determination becomes insufficient
Solution Approach 1:
The patent replaces manual mechanical analysis with automated computer-based processing. The system automatically processes log data, extracts entity relationships, and generates reports without human intervention in the core analysis steps, thereby eliminating human error and improving determination accuracy.
Solution Approach 2:
The system creates standardized representations of entity relationships by copying and structuring data from multiple log sources into a unified format. This allows systematic analysis and comparison across different data sources, improving the reliability of relationship identification.
2Adaptability or versatility
If comprehensive data from multiple computing systems is analyzed, then relationship identification capability is improved, but data processing complexity increases
Solution Approach 1:
The patent implements a universal processing framework that handles log data from multiple different computing systems through standardized procedures. The system performs multiple functions including data collection, standardization, entity extraction, and relationship analysis within a single integrated platform, reducing overall complexity.
Solution Approach 2:
The system divides the complex task of multi-system analysis into discrete processing stages: data collection from individual systems, standardization of formats, entity extraction, relationship identification, and report generation. This segmentation makes the overall process more manageable and less complex.
3Measurement precision
If log data is standardized and enriched with additional information, then analysis accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary standardization and enrichment of log data during the initial processing stage. By pre-processing and structuring data before relationship analysis, the system avoids repeated processing operations and reduces overall analysis time while maintaining high accuracy.
Data Source
AI summary
Systems and methods are provided for obtaining information from at least one computing system, the information including a set of records that respectively identify at least a network-based address of a computing device that accessed the computing system and an account hosted by the computing system that was accessed using the computing device; determining at least a first account and a second account were accessed from one or more computing devices that share a given network-based address based at least in part on the obtained information; and associating the first account and the second account with the network-based address.