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Article: Combating Coordinated Pricing Cyberattack and Energy Theft in Smart Home Cyber-Physical Systems

TitleCombating Coordinated Pricing Cyberattack and Energy Theft in Smart Home Cyber-Physical Systems
Authors
KeywordsContinuous state partially observable Markov decision process (POMDP)
coordinated cyberattacks
cross entropy state sampling
Fourier series belief state approximation
smart home cyber-physical system (CPS)
Issue Date2018
Citation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018, v. 37, n. 3, p. 573-586 How to Cite?
AbstractThe information exchange between the utility company and the smart community is crucial to the smart home cyber-physical systems. Yet the interaction between the two parties is vulnerable to many potential cyberattacks, among which the most striking ones are pricing cyberattacks and energy theft. Coordinated cyberattacks have emerged as an advanced attacking scheme with both pricing attack and energy theft applied in the cooperative manner, which can induce significant impact to smart home systems even if each attack is applied with only moderate strength. Such attacks cannot be effectively detected since the existing techniques are designed for detecting either pricing attack or energy theft without considering the impact due to coordinated attacks. This paper aims at developing the detection framework for coordinated cyberattacks considering coordinated impacts of various attacking strategies using an advanced continuous state partially observable Markov decision process. Handling coordinated attacks induces drastic increase in time complexity, which motivates us to propose innovative cross entropy state sampling and Fourier belief state approximation for the solving of developed detection framework. Our simulation results demonstrate that the coordinated cyberattack can reduce his/her electricity bill by 32.65%. In addition, the proposed detection technique can better capture coordinated attacks than the conventional detection technique, resulting in 10.31% increase in the hacker's bill.
Persistent Identifierhttp://hdl.handle.net/10722/336408
ISSN
2022 Impact Factor: 2.9
2020 SCImago Journal Rankings: 0.556
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yang-
dc.contributor.authorZhou, Yuchen-
dc.contributor.authorHu, Shiyan-
dc.date.accessioned2024-01-15T08:26:38Z-
dc.date.available2024-01-15T08:26:38Z-
dc.date.issued2018-
dc.identifier.citationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018, v. 37, n. 3, p. 573-586-
dc.identifier.issn0278-0070-
dc.identifier.urihttp://hdl.handle.net/10722/336408-
dc.description.abstractThe information exchange between the utility company and the smart community is crucial to the smart home cyber-physical systems. Yet the interaction between the two parties is vulnerable to many potential cyberattacks, among which the most striking ones are pricing cyberattacks and energy theft. Coordinated cyberattacks have emerged as an advanced attacking scheme with both pricing attack and energy theft applied in the cooperative manner, which can induce significant impact to smart home systems even if each attack is applied with only moderate strength. Such attacks cannot be effectively detected since the existing techniques are designed for detecting either pricing attack or energy theft without considering the impact due to coordinated attacks. This paper aims at developing the detection framework for coordinated cyberattacks considering coordinated impacts of various attacking strategies using an advanced continuous state partially observable Markov decision process. Handling coordinated attacks induces drastic increase in time complexity, which motivates us to propose innovative cross entropy state sampling and Fourier belief state approximation for the solving of developed detection framework. Our simulation results demonstrate that the coordinated cyberattack can reduce his/her electricity bill by 32.65%. In addition, the proposed detection technique can better capture coordinated attacks than the conventional detection technique, resulting in 10.31% increase in the hacker's bill.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems-
dc.subjectContinuous state partially observable Markov decision process (POMDP)-
dc.subjectcoordinated cyberattacks-
dc.subjectcross entropy state sampling-
dc.subjectFourier series belief state approximation-
dc.subjectsmart home cyber-physical system (CPS)-
dc.titleCombating Coordinated Pricing Cyberattack and Energy Theft in Smart Home Cyber-Physical Systems-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCAD.2017.2717781-
dc.identifier.scopuseid_2-s2.0-85021831743-
dc.identifier.volume37-
dc.identifier.issue3-
dc.identifier.spage573-
dc.identifier.epage586-
dc.identifier.isiWOS:000425674700005-

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