Analysis Support Device for Reducing Redundant Event Data Processing
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Solution Overview
Problem
Conventional analysis support methods perform unnecessary analyses on raw data related to events in monitored objects, leading to an increase in the number of analyses and resource consumption.
Innovation Solution
An analysis support method that communicates with monitored objects or databases to obtain raw data and outputs previous analysis results for similar data, reducing the need for redundant analyses by collating and scoring data entries to determine similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional analysis support methods analyze all raw data related to events in monitored objects, then analysis completeness is improved, but the number of analyses and resource consumption increase
Solution Approach 1:
The system performs preliminary actions by storing analysis results of previously obtained raw data in a database. When new raw data is obtained, the system first checks if similar data exists in the database before performing new analysis, thereby avoiding redundant analysis work while maintaining analysis completeness.
Solution Approach 2:
The system creates and utilizes copies of previously analyzed data and their corresponding analysis results. By storing raw data and analysis results in a database, the system can retrieve and reuse these copies instead of re-analyzing identical or similar data, significantly improving analysis efficiency.
2Measurement precision
If conventional analysis support methods perform analysis on every raw data event, then analysis accuracy is maintained, but resource utilization increases
Solution Approach 1:
The system implements a feedback mechanism where analysis results are stored in a database and fed back into the system. When new raw data arrives, the system compares it with previously analyzed data in the database, using this feedback to determine whether new analysis is necessary, thereby maintaining accuracy while reducing resource consumption.
Solution Approach 2:
The system performs preliminary comparison actions by checking the database for similar raw data before committing to full analysis. This preliminary action filters out redundant analysis cases, ensuring that analysis accuracy is maintained only when necessary, thus optimizing resource utilization.
3Reliability
If conventional analysis support methods re-analyze similar raw data, then analysis thoroughness is improved, but the number of redundant analyses increases
Solution Approach 1:
The system creates copies of previously analyzed data and stores them in a database. When new raw data is obtained, the system retrieves and compares these copies to identify identical or similar data, avoiding redundant analysis and reducing analysis time while maintaining thoroughness through selective re-analysis when necessary.
Solution Approach 2:
The system performs preliminary comparison actions by checking the database for similar raw data before performing new analysis. This preliminary step filters out redundant cases, reducing analysis time while ensuring thoroughness is maintained for unique or significantly different data through selective new analysis.
Data Source
AI summary
An analysis support method is performed by an analysis support device that supports an analysis of an attack scenario in an event that has occurred in a monitored object, and the analysis is performed based on raw data related to the event. The analysis support method includes: obtaining the raw data by communicating with the monitored object or communicating with a database that stores the raw data obtained from the monitored object; and outputting a previous analysis result for previously obtained raw data that is similar to the raw data obtained.