File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Impact assessment of net metering on smart home cyberattack detection

TitleImpact assessment of net metering on smart home cyberattack detection
Authors
KeywordsCyberattack
Net Metering
Renewable Energy
Smart Home
Stochastic Optimization
Issue Date2015
Citation
Proceedings - Design Automation Conference, 2015, v. 2015-July, article no. 7167281 How to Cite?
AbstractDespite the increasing popularity of the smart home concept, such a technology is vulnerable to various security threats such as pricing cyberattacks. There are some technical advances in developing detection and defense frameworks against those pricing cyberattacks. However, none of them considers the impact of net metering, which allows the customers to sell the excessively generated renewable energy back to the grid. At a superficial glance, net metering seems to be irrelevant to the cybersecurity, while this paper demonstrates that its implication is actually profound. In this paper, we propose to analyze the impact of the net metering technology on the smart home pricing cyberattack detection. Net metering changes the grid energy demand, which is considered by the utility when designing the guideline price. Thus, cyberattack detection is compromised if this impact is not considered. It motivates us to develop a new smart home pricing cyberattack detection framework which judiciously integrates the net metering technology with the short/long term detection. The simulation results demonstrate that our new framework can significantly improve the detection accuracy from 65.95% to 95.14% compared to the state-of-art detection technique.
Persistent Identifierhttp://hdl.handle.net/10722/336146
ISSN
2020 SCImago Journal Rankings: 0.518
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yang-
dc.contributor.authorHu, Shiyan-
dc.contributor.authorWu, Jie-
dc.contributor.authorShi, Yiyu-
dc.contributor.authorJin, Yier-
dc.contributor.authorHu, Yu-
dc.contributor.authorLi, Xiaowei-
dc.date.accessioned2024-01-15T08:23:54Z-
dc.date.available2024-01-15T08:23:54Z-
dc.date.issued2015-
dc.identifier.citationProceedings - Design Automation Conference, 2015, v. 2015-July, article no. 7167281-
dc.identifier.issn0738-100X-
dc.identifier.urihttp://hdl.handle.net/10722/336146-
dc.description.abstractDespite the increasing popularity of the smart home concept, such a technology is vulnerable to various security threats such as pricing cyberattacks. There are some technical advances in developing detection and defense frameworks against those pricing cyberattacks. However, none of them considers the impact of net metering, which allows the customers to sell the excessively generated renewable energy back to the grid. At a superficial glance, net metering seems to be irrelevant to the cybersecurity, while this paper demonstrates that its implication is actually profound. In this paper, we propose to analyze the impact of the net metering technology on the smart home pricing cyberattack detection. Net metering changes the grid energy demand, which is considered by the utility when designing the guideline price. Thus, cyberattack detection is compromised if this impact is not considered. It motivates us to develop a new smart home pricing cyberattack detection framework which judiciously integrates the net metering technology with the short/long term detection. The simulation results demonstrate that our new framework can significantly improve the detection accuracy from 65.95% to 95.14% compared to the state-of-art detection technique.-
dc.languageeng-
dc.relation.ispartofProceedings - Design Automation Conference-
dc.subjectCyberattack-
dc.subjectNet Metering-
dc.subjectRenewable Energy-
dc.subjectSmart Home-
dc.subjectStochastic Optimization-
dc.titleImpact assessment of net metering on smart home cyberattack detection-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/2744769.2747930-
dc.identifier.scopuseid_2-s2.0-84944104258-
dc.identifier.volume2015-July-
dc.identifier.spagearticle no. 7167281-
dc.identifier.epagearticle no. 7167281-
dc.identifier.isiWOS:000370268400098-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats