research-article

Impact assessment of net metering on smart home cyberattack detection

Authors:

Jie Wu,

Yu Hu,

Xiaowei LiAuthors Info & Claims

DAC '15: Proceedings of the 52nd Annual Design Automation Conference

Article No.: 97, Pages 1 - 6

https://doi.org/10.1145/2744769.2747930

Published: 07 June 2015 Publication History

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Abstract

Despite 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.

References

[1]

{Online}. Available: http://www.solarcity.com/learn/understanding-netmetering.aspx

Google Scholar

[2]

Distributed generation and renewable energy current programs for businesses. {Online}. Available: http://docs.cpuc.ca.gov/published/newsrelease/7408.htm

Google Scholar

[3]

Z. I. Botev, D. P. Kroese, R. Y. Rubinstein, et al. The cross entropy method for optimization. Machine Learning: Theory and Applications, V. Govindaraju and C. R. Rao, Eds, Chennai: Elsevier BV, 31:35--59, 2013.

Google Scholar

[4]

L. P. Kaelbling, M. L. Littman, and A. Cassandra. Planning and acting in partially observable stochastic domains. Artificial Intelligence, pages 99--134, 1998.

Digital Library

Google Scholar

[5]

B. Li, S. Gangadhar, S. Cheng, and P. Verma. Maximize user rewards in distributed generation environments using reinforcement learning. In Proceedings of IEEE Energytech, pages 1--6, 2011.

Google Scholar

[6]

L. Liu, Y. Zhou, Y. Liu, and S. Hu. Dynamic programming based game theoretic algorithm for economical multi-user smart home scheduling. In Proceedings of IEEE Midwest Symposium on Circuits and Systems, pages 362--365, 2014.

Crossref

Google Scholar

[7]

Y. Liu, S. Hu, and T.-Y. Ho. Leveraging strategic defense techniques for smart home pricing cyberattacks. Accepted to IEEE Transactions on Dependable and Secure Computing.

Google Scholar

[8]

Y. Liu, S. Hu, and T.-Y. Ho. Vulnerability assessment and defense technology for smart home cybersecurity considering pricing cyberattacks. In Proceedings of IEEE/ACM International Conference on Computer-Aided Design, pages 183--190, 2014.

Digital Library

Google Scholar

[9]

A. Mohsenian-Rad, V. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia. Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1(3):320--331, 2010.

Crossref

Google Scholar

[10]

K. Tuomas, F. Rossi, and A. Lendasse. Ls-svm functional network for time series prediction. In Proceedings of European Symposium on Artificial Neural Networks, 2006.

Google Scholar

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Graveto VCruz TSimöes P(2022)Security of Building Automation and Control SystemsComputers and Security10.1016/j.cose.2021.102527112:COnline publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102527
Pazouki SK C BAlkhwaildi HAsrari A(2021)Modelling of Smart Homes Affected by Cyberattacks2020 52nd North American Power Symposium (NAPS)10.1109/NAPS50074.2021.9449777(1-6)Online publication date: 11-Apr-2021
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https://doi.org/10.1109/TSC.2020.2964548
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Impact assessment of net metering on smart home cyberattack detection

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DAC '15: Proceedings of the 52nd Annual Design Automation Conference

June 2015

1204 pages

ISBN:9781450335201

DOI:10.1145/2744769

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 June 2015

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DAC '15: The 52nd Annual Design Automation Conference 2015

June 7 - 11, 2015

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Graveto VCruz TSimöes P(2022)Security of Building Automation and Control SystemsComputers and Security10.1016/j.cose.2021.102527112:COnline publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102527
Pazouki SK C BAlkhwaildi HAsrari A(2021)Modelling of Smart Homes Affected by Cyberattacks2020 52nd North American Power Symposium (NAPS)10.1109/NAPS50074.2021.9449777(1-6)Online publication date: 11-Apr-2021
https://doi.org/10.1109/NAPS50074.2021.9449777
Mu LZhao EWang YZomaya A(2020)Buoy Sensor Cyberattack Detection in Offshore Petroleum Cyber-Physical SystemsIEEE Transactions on Services Computing10.1109/TSC.2020.296454813:4(653-662)Online publication date: 1-Jul-2020
https://doi.org/10.1109/TSC.2020.2964548
Chhetri CMotti V(2020)Identifying Vulnerabilities in Security and Privacy of Smart Home DevicesNational Cyber Summit (NCS) Research Track 202010.1007/978-3-030-58703-1_13(211-231)Online publication date: 9-Sep-2020
https://doi.org/10.1007/978-3-030-58703-1_13
Li BWu JShi Y(2019)Privacy-Aware Cost-Effective Scheduling Considering Non-Schedulable Appliances in Smart Home2019 IEEE International Conference on Embedded Software and Systems (ICESS)10.1109/ICESS.2019.8782440(1-8)Online publication date: Jun-2019
https://doi.org/10.1109/ICESS.2019.8782440
Liu YZhou YHu S(2018)Combating Coordinated Pricing Cyberattack and Energy Theft in Smart Home Cyber-Physical SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2017.271778137:3(573-586)Online publication date: Mar-2018
https://doi.org/10.1109/TCAD.2017.2717781
Wurm JJin YLiu YHu SHeffner KRahman FTehranipoor M(2017)Introduction to Cyber-Physical System Security: A Cross-Layer PerspectiveIEEE Transactions on Multi-Scale Computing Systems10.1109/TMSCS.2016.25694463:3(215-227)Online publication date: 1-Jul-2017
https://doi.org/10.1109/TMSCS.2016.2569446
Liu YHu SWu JShi YJin YHu YLi X(2016)Smart home cybersecurity considering the integration of renewable energySmart Cities and Homes10.1016/B978-0-12-803454-5.00009-2(173-189)Online publication date: 2016
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Konstantinou CManiatakos MSaqib FHu SPlusquellic JJin Y(2015)Cyber-physical systems: A security perspective2015 20th IEEE European Test Symposium (ETS)10.1109/ETS.2015.7138763(1-8)Online publication date: May-2015
https://doi.org/10.1109/ETS.2015.7138763

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