Cyber-attack detection and neutralization
Abstract
The example embodiments are directed to a system and method for neutralizing abnormal signals in a cyber-physical system. In one example, the method includes receiving input signals comprising time series data associated with an asset and transforming the input signals into feature values in a feature space, detecting one or more abnormal feature values in the feature space based on a predetermined normalcy boundary associated with the asset, and determining an estimated true value for each abnormal feature value, and performing an inverse transform of each estimated true value to generate neutralized signals comprising time series data and outputting the neutralized signals.
- Inventors:
- Issue Date:
- Research Org.:
- General Electric Co., Schenectady, NY (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1735249
- Patent Number(s):
- 10771495
- Application Number:
- 15/454,144
- Assignee:
- General Electric Company (Schenectady, NY)
- Patent Classifications (CPCs):
-
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: 03/09/2017
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Mestha, Lalit Keshav, Anubi, Olugbenga, and Abbaszadeh, Masoud. Cyber-attack detection and neutralization. United States: N. p., 2020.
Web.
Mestha, Lalit Keshav, Anubi, Olugbenga, & Abbaszadeh, Masoud. Cyber-attack detection and neutralization. United States.
Mestha, Lalit Keshav, Anubi, Olugbenga, and Abbaszadeh, Masoud. Tue .
"Cyber-attack detection and neutralization". United States. https://www.osti.gov/servlets/purl/1735249.
@article{osti_1735249,
title = {Cyber-attack detection and neutralization},
author = {Mestha, Lalit Keshav and Anubi, Olugbenga and Abbaszadeh, Masoud},
abstractNote = {The example embodiments are directed to a system and method for neutralizing abnormal signals in a cyber-physical system. In one example, the method includes receiving input signals comprising time series data associated with an asset and transforming the input signals into feature values in a feature space, detecting one or more abnormal feature values in the feature space based on a predetermined normalcy boundary associated with the asset, and determining an estimated true value for each abnormal feature value, and performing an inverse transform of each estimated true value to generate neutralized signals comprising time series data and outputting the neutralized signals.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {9}
}
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