Scalable hierarchical abnormality localization in cyber-physical systems
Abstract
A cyber-physical system may have monitoring nodes that generate a series of current monitoring node values over time that represent current operation of the system. A hierarchical abnormality localization computer platform accesses a multi-level hierarchy of elements, and elements in a first level of the hierarchy are associated with elements in at least one lower level of the hierarchy and at least some elements may be associated with monitoring nodes. The computer platform may then determine, based on feature vectors and a decision boundary, an abnormality status for a first element in the highest level of the hierarchy. If the abnormality status indicates an abnormality, the computer platform may determine an abnormality status for elements, associated with the first element, in at least one level of the hierarchy lower than the level of the first element. These determinations may be repeated until an abnormality is localized to a monitoring node.
- Inventors:
- Issue Date:
- Research Org.:
- General Electric Co., Schenectady, NY (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1986819
- Patent Number(s):
- 11503045
- Application Number:
- 16/261,931
- Assignee:
- General Electric Company (Schenectady, NY)
- DOE Contract Number:
- OE0000833
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 01/30/2019
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Abbaszadeh, Masoud, Yund, Walter, and Holzhauer, Daniel Francis. Scalable hierarchical abnormality localization in cyber-physical systems. United States: N. p., 2022.
Web.
Abbaszadeh, Masoud, Yund, Walter, & Holzhauer, Daniel Francis. Scalable hierarchical abnormality localization in cyber-physical systems. United States.
Abbaszadeh, Masoud, Yund, Walter, and Holzhauer, Daniel Francis. Tue .
"Scalable hierarchical abnormality localization in cyber-physical systems". United States. https://www.osti.gov/servlets/purl/1986819.
@article{osti_1986819,
title = {Scalable hierarchical abnormality localization in cyber-physical systems},
author = {Abbaszadeh, Masoud and Yund, Walter and Holzhauer, Daniel Francis},
abstractNote = {A cyber-physical system may have monitoring nodes that generate a series of current monitoring node values over time that represent current operation of the system. A hierarchical abnormality localization computer platform accesses a multi-level hierarchy of elements, and elements in a first level of the hierarchy are associated with elements in at least one lower level of the hierarchy and at least some elements may be associated with monitoring nodes. The computer platform may then determine, based on feature vectors and a decision boundary, an abnormality status for a first element in the highest level of the hierarchy. If the abnormality status indicates an abnormality, the computer platform may determine an abnormality status for elements, associated with the first element, in at least one level of the hierarchy lower than the level of the first element. These determinations may be repeated until an abnormality is localized to a monitoring node.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {11}
}
Works referenced in this record:
Hybrid Method for Anomaly Classification
patent-application, July 2017
- Limonad, Lior; Mashkif, Nir; Wasserkrug, Segev E.
- US Patent Application 14/988766; 20170193078
Cluster-based decision boundaries for threat detection in industrial asset control system
patent-application, July 2018
- Abbaszadeh, Masoud; Bushey, Cody Joe; Mestha, Lalit Keshav
- US Patent Application 15/397062; 20180191758
Systems and methods for improving the ranking and prioritization of attack-related events
patent, August 2020
- Aloisio, Scott; Joyce, Robert A.; Powers, Judson
- US Patent Document 10,749,890