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Title: 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
Subject:
97 MATHEMATICS AND COMPUTING

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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