Cyber-Physical System Anomaly Detection Using Auxiliary Variables
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Solution Overview
Problem
Existing anomaly detection systems in cyber-physical systems (CPS) primarily focus on critical data and do not effectively utilize auxiliary variables derived from primary CPS variables, which can carry more informative synthetic data, leading to incomplete anomaly detection due to noise in raw data and lack of consideration for derivatives and integrated transformations.
Innovation Solution
The method generates diagnostic rules to calculate auxiliary CPS variables from primary variables, using techniques such as smoothing, trend analysis, and machine learning models to enhance anomaly detection by considering both primary and auxiliary variables, thereby improving the accuracy of anomaly identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If anomaly detection systems only use primary critical data from ACS TP, then the system complexity remains low, but the measurement precision and reliability of anomaly detection deteriorates due to noise in raw data and lack of informative synthetic data
Solution Approach 1:
The patent introduces auxiliary CPS variables as intermediary elements that mediate between primary CPS variables and anomaly detection. These auxiliary variables are calculated using diagnostic rules that process primary variables through smoothing, trend analysis, and other transformations. The intermediary auxiliary variables filter noise while preserving anomaly information, thereby improving detection accuracy without directly increasing system complexity
Solution Approach 2:
The system performs preliminary processing of primary CPS variables by calculating auxiliary variables in advance before anomaly detection. Diagnostic rules pre-process the raw data through smoothing, window analysis, and trend calculations, preparing refined data that reduces noise and enhances anomaly visibility. This preliminary action prevents the need for complex real-time processing during anomaly detection
2Reliability
If external monitoring systems are deployed at all critical nodes, then the coverage and reliability of monitoring improves, but the cost and device complexity increases significantly
Solution Approach 1:
The patent creates a universal anomaly detection system that integrates with the existing ACS TP and can monitor the entire enterprise through a single centralized platform. Instead of deploying separate external monitoring systems at each critical node, the unified system processes data from all CPS variables enterprise-wide, providing comprehensive monitoring coverage with a single multi-functional system that reduces overall deployment complexity
Solution Approach 2:
The patent merges the anomaly detection functionality with the existing automated control system for technological processes (ACS TP). By combining monitoring and control functions into a unified system that shares data infrastructure and processing resources, the patent achieves enterprise-wide monitoring coverage without the need for separate external monitoring systems at each node, thereby reducing deployment complexity while maintaining reliability
3Ease of operation
If emergency protection systems are used with simple architecture, then the ease of operation and response time improves, but the measurement precision deteriorates because EPS assumes faultless monitoring instruments which is not always true in practice
Solution Approach 1:
The system performs preliminary processing of monitoring data by calculating auxiliary CPS variables that are smoothed and filtered versions of primary variables. This pre-processing prepares refined data that is more robust to instrument failures and noise, allowing the simple EPS architecture to operate with higher measurement precision without requiring complex redundant instrumentation
Solution Approach 2:
The patent introduces auxiliary variables as intermediary data elements that mediate between potentially faulty primary monitoring data and the emergency protection system decisions. These intermediary variables are calculated using diagnostic rules that account for instrument reliability issues, providing more accurate input to the EPS while maintaining its simple architecture and ease of operation
Data Source
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AI summary
A method for determination of anomalies in a cyber-physical system (CPS) includes generating one or more diagnostic rules configured to calculate at least one auxiliary CPS variable. One or more values of the at least one auxiliary CPS variable are calculated for a predefined output interval of time based on collected values of a group of primary CPS variables for a predefined input interval of time based on the generated diagnostic rule. An anomaly is determined based on the collected values of the group of primary CPS variables and the one or more calculated values of the at least one auxiliary CPS variable.