Opportunistic Sensor Correlation for Industrial Security Alerts
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Solution Overview
Problem
Industrial operations face increasing data breaches that disrupt operations, cause equipment damage, and pose safety risks, with existing security and safety measures failing to detect anomalies effectively.
Innovation Solution
A method and component that utilize opportunistic sensing to derive a baseline signature from sensor information, identify abnormal operating conditions, and correlate them with abnormal data traffic conditions, sending security alerts to mitigate potential threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional security measures are used to monitor industrial operations, then system simplicity is maintained, but detection precision of security anomalies is insufficient
Solution Approach 1:
The patent reuses existing sensor information that is already collected for operational functionality and repurposes it for security anomaly detection. This multi-functional use of sensor data eliminates the need for separate dedicated security sensors, thereby improving detection precision without proportionally increasing system complexity
Solution Approach 2:
The patent combines operational sensor data monitoring with security anomaly detection into a unified analysis framework. By merging these functions and analyzing sensor data through both operational and security lenses simultaneously, the system achieves enhanced anomaly detection while avoiding the overhead of completely separate monitoring systems
2Reliability
If existing anomaly detection systems are deployed, then some security threats are detected, but correlation between operating conditions and data traffic anomalies is missed
Solution Approach 1:
The patent establishes a feedback loop that continuously compares sensor information against baseline signatures and correlates abnormal operating conditions with abnormal data traffic patterns. This feedback mechanism enables the system to refine its detection accuracy over time and maintain reliable threat detection by leveraging correlations between operational and network anomalies
Solution Approach 2:
The patent pre-establishes baseline signatures representing normal operational patterns before security incidents occur. By having these baselines ready in advance, the system can quickly compare actual sensor data against expected patterns and immediately identify deviations, preventing information loss during critical security events
Data Source
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AI summary
A method for security and safety of an industrial operation includes receiving sensor information from a plurality of sensors of an industrial operation. Sensor information from at least a portion of the plurality sensors is used for functionality of a plurality of components of the industrial operation. The method includes monitoring data traffic of the industrial operation, and deriving a baseline signature from the sensor information. The baseline signature encompasses a range of normal operating conditions. The method includes identifying an abnormal operating condition of the industrial operation based on a comparison between additional sensor information from the plurality of sensors and the baseline signature and identifying an abnormal data traffic condition. The method includes determining that the abnormal operating condition correlates to the abnormal data traffic condition, and sending a security alert in response to determining that the abnormal operating condition correlates to the abnormal data traffic condition.