Signal Filtering Tool for Security Event Correlation
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Solution Overview
Problem
Managing and correlating disparate security signals from various sources is challenging, making it difficult to establish their correlation, especially when dealing with potential security threats or anomalies in computer performance, which complicates the troubleshooting process.
Innovation Solution
A filtering tool that allows users to customize correlation parameters, utilize exact match, extended match, and AI match modes to identify relevant signals associated with a given event, providing a user interface with filters for type, severity, and tag filters, and automatically identifies upstream and downstream events to group related signals together.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple filtering options and AI match modes are added to improve signal correlation accuracy, then the device complexity increases
Solution Approach 1:
The filtering tool is segmented into multiple independent filtering modes (exact match, extended match, AI match) that can be selected based on specific needs. Each mode implements a distinct filtering algorithm, allowing the system to provide high measurement precision through specialized methods without requiring all methods to run simultaneously, thus managing device complexity through modular segmentation.
Solution Approach 2:
The filtering tool implements dynamic adaptability by allowing users to switch between different filtering modes and adjust correlation parameters in real-time. The AI match mode dynamically learns from data patterns and adapts filtering criteria, enabling the system to maintain high accuracy across varying conditions while keeping the interface unified and manageable.
2Productivity
If comprehensive filtering options are provided to improve troubleshooting effectiveness, then the ease of operation decreases
Solution Approach 1:
Instead of requiring users to configure complex filtering parameters manually, the AI match mode inverts the approach by automatically analyzing signals and intelligently selecting relevant correlations. This reduces the operational burden on users while maintaining comprehensive filtering capabilities, as the system performs the complex configuration work autonomously based on learned patterns.
Solution Approach 2:
The filtering tool provides self-service capabilities through preset filtering configurations and AI-driven automatic signal correlation. The system automatically identifies relevant signals and applies appropriate filtering criteria without requiring users to manually configure each parameter, thereby maintaining high troubleshooting effectiveness while simplifying the user interaction model.
3Measurement precision
If AI filters and matching scores are implemented to improve signal identification accuracy, then the loss of time in processing increases
Solution Approach 1:
The system implements partial action by allowing users to adjust the score threshold parameter that determines which AI-matched signals are displayed. By setting an appropriate threshold, users can balance between comprehensive identification (lower threshold, more results, more time) and focused identification (higher threshold, fewer results, less time). This enables optimized processing time while maintaining sufficient identification accuracy for specific use cases.
Data Source
AI summary
A filtering tool identifies relevant signals associated with a given event (e.g., an alert) to facilitate analysis and decision-making for problem resolution. Users select the problem to be analyzed and the tool assists to determine the cause of the problem by analyzing, not only the events associated with an alert, but also other potential correlated events. The tool allows the adjustment of correlation parameters to present the desired information and offers options to focus on alert-related events, e.g., problems occurring simultaneously in other similar machines. The tool provides faceted search filters, which enable users to refine their search results based on configurable criteria. The inclusion of multiple filter types provides flexibility and enhances the user experience by facilitating easy refinement of search results.