Security Event Correlation and Dynamic Alarm Prioritization
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Solution Overview
Problem
Current security management systems fail to identify semantic correlations between security events and adapt alarm prioritization to contextual conditions, leading to high cognitive load for operators and inefficient response processes.
Innovation Solution
The Advanced Security Event Management (ASEM) system correlates security events using a modular approach with input, processing, and output levels, incorporating modules for event grouping, spatial and temporal reasoning, and dynamic alarm prioritization, along with self-learning and adaptation, to provide semantic alarms and adaptive prioritization based on contextual conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security management systems gather information from multiple sources and present alerts, then security monitoring capability is improved, but operator cognitive load increases and response efficiency decreases
Solution Approach 1:
The patent merges multiple security events and alerts into unified semantic alarms by correlating events across different sources (access control, intrusion detection, video management, etc.). This consolidation reduces the number of separate alerts operators must process while maintaining comprehensive security monitoring through the event correlation engine that integrates information from multiple sources.
Solution Approach 2:
The system introduces an intermediary processing layer consisting of the event correlation engine and semantic alarm generator. This intermediary layer sits between raw security events from multiple sources and operator decision-making, automatically performing event correlation, semantic interpretation, and prioritization to reduce cognitive load while maintaining monitoring reliability.
2Device complexity
If fixed alarm priority levels are used, then system simplicity is maintained, but adaptability to contextual conditions deteriorates
Solution Approach 1:
The patent implements dynamic alarm prioritization where the system automatically adjusts alarm priorities based on contextual conditions such as time of day, historical data, event patterns, and operational environment. The prioritization engine continuously learns from historical responses and adapts priority levels in real-time, transforming static priority schemes into dynamic, context-aware prioritization without significantly increasing system complexity.
Solution Approach 2:
The system incorporates feedback mechanisms where historical data about past security events and operator responses is used to refine future prioritization decisions. The event correlation engine analyzes historical patterns to automatically adjust priority assignments, creating a self-improving system that adapts to changing contextual conditions while maintaining relatively simple operation.
3Speed
If security events are processed independently, then processing speed is maintained, but correlation of semantic relationships is lost
Solution Approach 1:
The system performs preliminary event correlation and semantic analysis during the event processing stage rather than requiring separate post-processing. The event correlation engine immediately correlates related events from different sources as they arrive, building semantic relationships in advance so that when alerts are generated, the contextual relationships are already established, maintaining processing speed while preserving correlation information.
Solution Approach 2:
The patent maintains continuous event correlation and semantic analysis throughout the processing pipeline. Rather than processing events independently and then attempting to correlate them later, the system continuously correlates events as they are ingested, processed, and transformed into semantic alarms, ensuring that semantic relationships are preserved throughout the entire processing sequence without creating processing bottlenecks.
Data Source
AI summary
A system receives input from a plurality of sensors in a security management system. The input relates to two or more events. The input is stored in a database. A correlation between the two or more events is determined. A priority is dynamically assigned to the two or more events, and the correlation, the priority, and information relating to the two or more events are reported to a system user.