Learning method and system for separating independent and dependent attacks
Abstract
Streams of monitoring node signal values over time, representing a current operation of the industrial asset, are used to generate current monitoring node feature vectors. Each feature vector is compared with a corresponding decision boundary separating normal from abnormal states. When a first monitoring node passes a corresponding decision boundary, an attack is detected and classified as an independent attack. When a second monitoring node passes a decision boundary, an attack is detected and a first decision is generated based on a first set of inputs indicating if the attack is independent/dependent. From the beginning of the attack on the second monitoring node until a final time, the first decision is updated as new signal values are received for the second monitoring node. When the final time is reached, a second decision is generated based on a second set of inputs indicating if the attack is independent/dependent.
- Inventors:
- Issue Date:
- Research Org.:
- General Electric Co., Schenectady, NY (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1735308
- Patent Number(s):
- 10785237
- Application Number:
- 15/977,558
- 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: 05/11/2018
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Mestha, Lalit Keshav, Abbaszadeh, Masoud, and Giani, Annartia. Learning method and system for separating independent and dependent attacks. United States: N. p., 2020.
Web.
Mestha, Lalit Keshav, Abbaszadeh, Masoud, & Giani, Annartia. Learning method and system for separating independent and dependent attacks. United States.
Mestha, Lalit Keshav, Abbaszadeh, Masoud, and Giani, Annartia. Tue .
"Learning method and system for separating independent and dependent attacks". United States. https://www.osti.gov/servlets/purl/1735308.
@article{osti_1735308,
title = {Learning method and system for separating independent and dependent attacks},
author = {Mestha, Lalit Keshav and Abbaszadeh, Masoud and Giani, Annartia},
abstractNote = {Streams of monitoring node signal values over time, representing a current operation of the industrial asset, are used to generate current monitoring node feature vectors. Each feature vector is compared with a corresponding decision boundary separating normal from abnormal states. When a first monitoring node passes a corresponding decision boundary, an attack is detected and classified as an independent attack. When a second monitoring node passes a decision boundary, an attack is detected and a first decision is generated based on a first set of inputs indicating if the attack is independent/dependent. From the beginning of the attack on the second monitoring node until a final time, the first decision is updated as new signal values are received for the second monitoring node. When the final time is reached, a second decision is generated based on a second set of inputs indicating if the attack is independent/dependent.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {9}
}
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