Access Control Event Processing Engine for Threat Prioritization
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Solution Overview
Problem
Previous access control systems lack the intelligence to discover patterns and prioritize events that require immediate attention from security personnel, often leading to inefficiencies due to nuisance alerts, causing security personnel to respond to non-essential alerts instead of focusing on potential security threats.
Innovation Solution
An access control system that processes access control events using an event processing engine, which includes machine learning models to identify patterns and automate the escalation of potential security threats while suppressing nuisance alerts, by analyzing events from various devices such as card readers, biometric readers, and cameras, and determining whether to generate alarms based on predefined patterns and user profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If access control systems generate alerts for all security events, then security personnel can be notified of all potential threats, but security personnel are overwhelmed by nuisance alerts and cannot focus on critical threats
Solution Approach 1:
The patent introduces an event processing engine as an intermediary between access control events and security personnel. This engine analyzes events using machine learning models to determine whether they represent actual threats or nuisance alerts, filtering and prioritizing information before presenting it to security personnel. The engine acts as a mediator that reduces the information overload while maintaining reliable threat detection.
Solution Approach 2:
The system implements self-service through automated event analysis and prioritization. The event processing engine autonomously evaluates access control events, compares them against learned patterns, and determines alert generation without human intervention. This self-service capability reduces the manual workload of security personnel who would otherwise need to manually assess every alert.
2Adaptability or versatility
If access control systems use simple event processing, then the system is easier to operate and maintain, but the system lacks intelligence to discover patterns and prioritize events
Solution Approach 1:
The patent segments the access control system into distinct functional components: access control devices that generate events, an event processing engine that analyzes events, and machine learning models that provide pattern recognition intelligence. This segmentation allows the complex pattern recognition capabilities to be isolated in the event processing engine while keeping the rest of the system relatively simple and easy to operate.
Solution Approach 2:
The event processing engine serves as an intermediary layer that adds intelligent pattern recognition capabilities without requiring changes to the existing access control devices or infrastructure. By placing the machine learning models in this intermediate layer, the system gains advanced adaptability while maintaining the simplicity of the underlying access control system.
3Reliability
If security personnel respond to all alerts, then no potential threats are missed, but response time to critical threats increases due to handling nuisance alerts
Solution Approach 1:
The event processing engine performs preliminary analysis of access control events before they are presented to security personnel. By pre-evaluating events using machine learning models and determining which ones represent actual threats, the system prepares prioritized information in advance. This preliminary action ensures that when security personnel do respond, they are focusing on confirmed threats, completing their response task faster while maintaining completeness.
Solution Approach 2:
The system implements feedback loops where the event processing engine continuously learns from analyzed events and adjusts its pattern recognition capabilities. This feedback mechanism improves the accuracy of threat versus nuisance alert differentiation over time, reducing false positives and ensuring that security personnel receive increasingly accurate prioritized alerts that maintain response completeness while reducing time loss.
Data Source
AI summary
A method in a building access control system includes receiving a first access control event from a sensor indicating a door has been forced open or has been held open for at least a predetermined amount of time, identifying a second access control event associated with the door, determining whether to generate an alarm by evaluating the second access control event relative to the first access control event, and providing the alarm to a user of the access control system responsive to a determination that the alarm should be generated.