Industrial Asset Control Using Cyber-Attack Impact Prediction
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Solution Overview
Problem
Industrial assets, particularly those in renewable energy sectors like wind turbines, are vulnerable to cyber-attacks that can disrupt operations, reduce output quality, cause component wear, or lead to structural damage, resulting in increased costs and lost profits, with existing systems lacking effective detection and mitigation methods.
Innovation Solution
A method and system that generate a cyber-attack model to predict operational impacts and corresponding mitigation responses, using a neutralization module to detect attacks, identify predicted impacts, and select appropriate responses to alter the operating state of the industrial asset, including filtering affected signals and using emulators to replace corrupted inputs and outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional control systems are used for industrial assets, then the system is simple and easy to operate, but the system is vulnerable to cyber-attacks and cannot detect or mitigate operational impacts
Solution Approach 1:
The system generates a cyber-attack model in advance that predicts multiple potential operational impacts before they occur. This preliminary modeling allows the system to prepare mitigation responses proactively rather than reactively, improving reliability without requiring complex real-time decision-making infrastructure
Solution Approach 2:
A neutralization module is introduced as an intermediary component between the cyber-attack model and the industrial asset control system. This module detects cyber-attacks, identifies predicted operational impacts, and selects appropriate mitigation responses, adding security functionality without requiring complete system redesign
2Difficulty of detecting and measuring
If no cyber-attack detection system is implemented, then the control system remains simple, but the system cannot detect or respond to cyber-attacks impacting asset operations
Solution Approach 1:
The system creates a virtual copy of the industrial asset's operational model (cyber-attack model) that simulates how the asset would respond to various cyber-attacks. This digital twin approach enables attack detection and impact prediction without requiring physical sensors or complex monitoring infrastructure on the actual asset
Solution Approach 2:
The cyber-attack model is trained in advance with a data set containing information about multiple potential cyber-attacks and their operational impacts. This pre-training enables the system to detect and respond to attacks without requiring complex real-time analysis algorithms
3Speed
If mitigation responses are not pre-defined and correlated, then the system remains simple to implement, but the system cannot quickly select appropriate responses to predicted operational impacts
Solution Approach 1:
Multiple potential mitigation responses are generated and correlated with predicted operational impacts in advance through model training. This pre-correlation creates a lookup structure that enables the neutralization module to quickly select appropriate responses during actual cyber-attack events without requiring complex real-time optimization algorithms
Solution Approach 2:
The cyber-attack model serves multiple functions simultaneously: it predicts operational impacts, correlates them with mitigation responses, and provides the basis for the neutralization module's decision-making. This multi-functionality reduces the need for separate specialized systems while maintaining fast response capabilities
Data Source
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AI summary
Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.