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Article: Cyber Inference System for Substation Anomalies Against Alter-and-Hide Attacks

TitleCyber Inference System for Substation Anomalies Against Alter-and-Hide Attacks
Authors
Issue Date2016
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59
Citation
IEEE Transactions on Power Systems, 2016 How to Cite?
AbstractAlarms reported to energy control centers are an indication of abnormal events caused by either weather interruptions, system errors, or possibly intentional anomalies. Although these initiating events are random, e.g., faults on transmission lines struck by lightning, the existence of electronically altered measurements may implicate the process to identify root causes of abnormal events. This paper is concerned with alter-andhide (AaH) attacks by tampering the actual measurements to normal states with the background of disruptive switching actions that hide the true values of local events from operators at the control center. A cyber inference system (CyIS) framework is proposed to synthesize all sequential, missing, or altered alarms of related substations against AaH attacks. The stochastic nature of such attack events is modeled with probabilities as an integer programming problem with multiple scenarios. The proposed method is utilized to verify alarm scenarios for a conclusion of the potential AaH attacks on the substations.
Persistent Identifierhttp://hdl.handle.net/10722/229184
ISSN
2015 Impact Factor: 3.342
2015 SCImago Journal Rankings: 4.126

 

DC FieldValueLanguage
dc.contributor.authorWang, C-
dc.contributor.authorTen, CW-
dc.contributor.authorHou, Y-
dc.contributor.authorGinter, A-
dc.date.accessioned2016-08-23T14:09:31Z-
dc.date.available2016-08-23T14:09:31Z-
dc.date.issued2016-
dc.identifier.citationIEEE Transactions on Power Systems, 2016-
dc.identifier.issn0885-8950-
dc.identifier.urihttp://hdl.handle.net/10722/229184-
dc.description.abstractAlarms reported to energy control centers are an indication of abnormal events caused by either weather interruptions, system errors, or possibly intentional anomalies. Although these initiating events are random, e.g., faults on transmission lines struck by lightning, the existence of electronically altered measurements may implicate the process to identify root causes of abnormal events. This paper is concerned with alter-andhide (AaH) attacks by tampering the actual measurements to normal states with the background of disruptive switching actions that hide the true values of local events from operators at the control center. A cyber inference system (CyIS) framework is proposed to synthesize all sequential, missing, or altered alarms of related substations against AaH attacks. The stochastic nature of such attack events is modeled with probabilities as an integer programming problem with multiple scenarios. The proposed method is utilized to verify alarm scenarios for a conclusion of the potential AaH attacks on the substations.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59-
dc.relation.ispartofIEEE Transactions on Power Systems-
dc.rightsIEEE Transactions on Power Systems. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleCyber Inference System for Substation Anomalies Against Alter-and-Hide Attacks-
dc.typeArticle-
dc.identifier.emailHou, Y: yhhou@hku.hk-
dc.identifier.authorityHou, Y=rp00069-
dc.description.naturepostprint-
dc.identifier.doi10.1109/TPWRS.2016.2574769-
dc.identifier.hkuros260913-
dc.publisher.placeUnited States-

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