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Title: Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system

Abstract

A plurality of monitoring nodes may each generate a time-series of current monitoring node values representing current operation of a cyber-physical system. A feature-based forecasting framework may receive the time-series of and generate a set of current feature vectors using feature discovery techniques. The feature behavior for each monitoring node may be characterized in the form of decision boundaries that separate normal and abnormal space based on operating data of the system. A set of ensemble state-space models may be constructed to represent feature evolution in the time-domain, wherein the forecasted outputs from the set of ensemble state-space models comprise anticipated time evolution of features. The framework may then obtain an overall features forecast through dynamic ensemble averaging and compare the overall features forecast to a threshold to generate an estimate associated with at least one feature vector crossing an associated decision boundary.

Inventors:
;
Issue Date:
Research Org.:
General Electric Co., Schenectady, NY (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1771595
Patent Number(s):
10826932
Application Number:
16/108,742
Assignee:
General Electric Company (Schenectady, NY)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
H - ELECTRICITY H04 - ELECTRIC COMMUNICATION TECHNIQUE H04L - TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
DOE Contract Number:  
OE0000833
Resource Type:
Patent
Resource Relation:
Patent File Date: 08/22/2018
Country of Publication:
United States
Language:
English

Citation Formats

Abbaszadeh, Masoud, and Mestha, Lalit Keshav. Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system. United States: N. p., 2020. Web.
Abbaszadeh, Masoud, & Mestha, Lalit Keshav. Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system. United States.
Abbaszadeh, Masoud, and Mestha, Lalit Keshav. Tue . "Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system". United States. https://www.osti.gov/servlets/purl/1771595.
@article{osti_1771595,
title = {Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system},
author = {Abbaszadeh, Masoud and Mestha, Lalit Keshav},
abstractNote = {A plurality of monitoring nodes may each generate a time-series of current monitoring node values representing current operation of a cyber-physical system. A feature-based forecasting framework may receive the time-series of and generate a set of current feature vectors using feature discovery techniques. The feature behavior for each monitoring node may be characterized in the form of decision boundaries that separate normal and abnormal space based on operating data of the system. A set of ensemble state-space models may be constructed to represent feature evolution in the time-domain, wherein the forecasted outputs from the set of ensemble state-space models comprise anticipated time evolution of features. The framework may then obtain an overall features forecast through dynamic ensemble averaging and compare the overall features forecast to a threshold to generate an estimate associated with at least one feature vector crossing an associated decision boundary.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {11}
}

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