Dynamic Alert Prioritization Using Disposition Code Classifiers
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Solution Overview
Problem
Current risk management systems face challenges in efficiently processing and prioritizing numerous alerts from various data sources, leading to resource-intensive operations and overwhelming security operators due to the lack of contextual information and prioritization of alerts.
Innovation Solution
A building security system that utilizes a dynamic prioritization engine to calculate alert risk scores based on alert types, contextual data, security interest, asset cost, and user-disposition codes, employing machine learning models like Bayesian networks to estimate probabilities and prioritize alerts effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the security platform processes a large volume of alerts from multiple data sources, then the system provides comprehensive threat monitoring, but the resource consumption increases significantly
Solution Approach 1:
The system performs preliminary alert prioritization and classification before human review, using automated algorithms to assess alert severity, context, and potential threats. This preliminary action filters and organizes alerts in advance, reducing the cognitive load and resource requirements for human operators while maintaining comprehensive monitoring coverage.
Solution Approach 2:
An intermediary alert prioritization layer is introduced between raw alert data and human operators. This layer includes automated classification systems, context enrichment modules, and risk assessment algorithms that process and pre-sort alerts, acting as a mediator that reduces information overload while preserving critical threat information for human review.
2Measurement precision
If security operators review each alert individually without context, then detailed assessment is possible, but the workload becomes overwhelming and timely disposition is difficult
Solution Approach 1:
Multiple alert attributes, contextual information, and risk factors are merged into a unified prioritized alert view. The system combines raw alert data with contextual enrichment, historical patterns, and risk assessments into a consolidated presentation that provides comprehensive assessment information while reducing the number of separate review actions required by operators.
Solution Approach 2:
The system adds temporal and contextual dimensions to alert presentation by showing alert history, pattern recognition, and risk trajectories alongside individual alerts. This dimensional enrichment allows operators to assess multiple alerts simultaneously with greater context, reducing the need to review each alert in isolation and decreasing overall workload.
3Device complexity
If alerts are presented without situational context, then the system remains simple, but operators cannot effectively prioritize or comprehend alert importance
Solution Approach 1:
Contextual information is gathered and prepared in advance before alert presentation to operators. The system pre-enriches alerts with relevant contextual data, historical patterns, and risk assessments, so that when operators receive alerts, the necessary context is already attached. This preliminary context preparation adds minimal system complexity while significantly improving alert comprehensibility and prioritization capability.
Data Source
AI summary
A building security system includes one or more memory devices configured to store instructions that, when executed by one or more processors, cause the one or more processors to receive multiple alerts relating to a building, the multiple alerts include alert types. The instructions further cause the one or more processors to identify a set of alert disposition options for the multiple alerts based on the alert types, and estimate probabilities of use for the set of alert disposition options. The instructions further cause the one or more processors to calculate alert disposition risk scores using the estimated probabilities of use of the set of alert disposition options, calculate alert risk scores based on a combination of the alert disposition risk scores for the set of alert disposition options of the multiple alerts, and present two or more of the multiple alerts based on the alert risk scores.