Query Strength Indicator for SIEM Search Optimization
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Solution Overview
Problem
Non-filtered searches of security logs by SIEM services can take hours or days to complete, affecting IT resources and users, and users often neglect filtering options due to lack of awareness about their benefits, leading to inefficient searches.
Innovation Solution
A query strength indicator is provided in the user interface that visually changes appearance based on the strength of the search request, encouraging users to apply filters before searching, thereby reducing resource consumption and improving search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users perform non-filtered searches of security logs, then comprehensive search coverage is achieved, but search time increases to hours or days and IT resources are heavily consumed
Solution Approach 1:
The system performs preliminary analysis of search criteria to calculate query strength and predict resource consumption before the search is executed. This allows the system to provide advance feedback to users about the potential impact of their search, enabling them to adjust filters beforehand to avoid excessive resource usage and time consumption.
Solution Approach 2:
The system implements a feedback mechanism that displays query strength indicators to users based on their search criteria. This feedback shows users how their search filters will impact search time and resource consumption, allowing them to make informed decisions about filter application. The feedback loop continues as users adjust filters, with the indicator updating in real-time to reflect the changing query strength.
2Productivity
If users apply search filters, then search speed and resource efficiency improve, but users may lack awareness of filter benefits and neglect filtering options
Solution Approach 1:
The query strength indicator provides immediate visual feedback to users about the effectiveness of their search filters. By displaying the indicator prominently and updating it as users add or remove filters, the system makes the benefits of filtering visible and tangible, helping users understand the direct impact of their actions on search efficiency and resource consumption.
Solution Approach 2:
The system uses color changes in the query strength indicator to communicate filter effectiveness intuitively. Different colors represent different levels of query strength, allowing users to quickly grasp the impact of their filtering decisions without needing to understand complex technical parameters. This visual cue system makes filter benefits immediately apparent and encourages proper filter usage.
3Reliability
If comprehensive searches are performed without filters, then all relevant data is retrieved, but IT resource consumption increases significantly affecting other users and services
Solution Approach 1:
The system performs preliminary evaluation of search queries by analyzing the search criteria and calculating query strength before execution. This preliminary action allows the system to identify searches that would consume excessive resources and provide users with feedback to optimize their filters, thereby reducing resource consumption while maintaining data completeness where possible.
Solution Approach 2:
The query strength indicator provides continuous feedback to users about the resource consumption implications of their search criteria. This feedback mechanism helps users understand the trade-off between data completeness and resource usage, enabling them to make informed decisions about filter application to achieve acceptable results with reduced resource consumption.
Data Source
AI summary
A user interface is presented that is configured for receiving a user search criteria and search filter limit for a search request. An indicator is presented. Presenting the indicator includes changing appearance of the indicator to indicate increasing strength of the search request.