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HYBRID UNSUPERVISED MACHINE LEARNING FRAMEWORK FOR INDUSTRIAL CONTROL SYSTEM INTRUSION DETECTION
HYBRID UNSUPERVISED MACHINE LEARNING FRAMEWORK FOR INDUSTRIAL CONTROL SYSTEM INTRUSION DETECTION
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机译:混合无监督机械学习框架工业控制系统入侵检测
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摘要
A system for monitoring an industrial system for cyberattacks includes an industrial control system including a plurality of actuators, a plurality of sensors each arranged to measure one of a plurality of operating parameters, and an edge device and a computer including a data storage device having stored thereon a program that includes each of a time-series database including expected operating ranges for each operating parameter, a clustering-based database that includes clusters of operating parameters having similarities, and a correlation database that includes pairs of operating parameters that show a correlation. An alarm system is operable to initiate an alarm in response to current operating data including a measurement from one of the plurality of sensors falling outside of an expected range, a change in the expected clustering of one of the plurality of sensors based on the current operating data from each of the plurality of sensors, and a variation in the current operating data between two of the plurality of sensors that falls outside of an expected correlation of the two of the plurality of sensors.
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