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Book Chapter: Smart home scheduling and cybersecurity: Fundamentals

TitleSmart home scheduling and cybersecurity: Fundamentals
Authors
KeywordsAdvanced metering infrastructure
Cybersecurity
Electricity-pricing manipulation
Partially observable Markov decision process
Single event detection
Smart home scheduling
Issue Date2016
Citation
Smart Cities and Homes: Key Enabling Technologies, 2016, p. 191-217 How to Cite?
AbstractThe modern power system is undergoing a transformative shift from the classical electricity grid to a smart grid. There are four components in a smart grid, namely, smart power generation, smart transmission, smart distribution, and smart end use. Among them, the smart home technique controls the energy consumption of each end user, also known as customer, which potentially impacts the energy generation, transmission, and distribution.The smart home infrastructure features the automatic control of various interconnected modern home appliances. Together with the salient scheduling algorithms, it enables the customers to schedule the energy consumption, thus avoiding using electricity energy during the peak hours. This results in the reduction of electricity bill from the customer's perspective and improved balance of the energy load from the utility's perspective. The aforementioned process involves the usage of guideline pricing which estimates the future electricity price added by smart home controller. Despite its effectiveness, the smart home system is vulnerable to malicious cyberattacks. A hacker can manipulate the received guideline price and mislead the schedulers to make wrong decisions of energy scheduling. This can impact the bills of the customers and the peak energy usage of the power system. This chapter presents the state-of-the-art research on the smart home scheduling technique, explores the vulnerability of the smart home infrastructure, and describes the recent development of detection technologies against those cyberattacks.
Persistent Identifierhttp://hdl.handle.net/10722/336165

 

DC FieldValueLanguage
dc.contributor.authorLiu, Y.-
dc.contributor.authorHu, S.-
dc.date.accessioned2024-01-15T08:24:05Z-
dc.date.available2024-01-15T08:24:05Z-
dc.date.issued2016-
dc.identifier.citationSmart Cities and Homes: Key Enabling Technologies, 2016, p. 191-217-
dc.identifier.urihttp://hdl.handle.net/10722/336165-
dc.description.abstractThe modern power system is undergoing a transformative shift from the classical electricity grid to a smart grid. There are four components in a smart grid, namely, smart power generation, smart transmission, smart distribution, and smart end use. Among them, the smart home technique controls the energy consumption of each end user, also known as customer, which potentially impacts the energy generation, transmission, and distribution.The smart home infrastructure features the automatic control of various interconnected modern home appliances. Together with the salient scheduling algorithms, it enables the customers to schedule the energy consumption, thus avoiding using electricity energy during the peak hours. This results in the reduction of electricity bill from the customer's perspective and improved balance of the energy load from the utility's perspective. The aforementioned process involves the usage of guideline pricing which estimates the future electricity price added by smart home controller. Despite its effectiveness, the smart home system is vulnerable to malicious cyberattacks. A hacker can manipulate the received guideline price and mislead the schedulers to make wrong decisions of energy scheduling. This can impact the bills of the customers and the peak energy usage of the power system. This chapter presents the state-of-the-art research on the smart home scheduling technique, explores the vulnerability of the smart home infrastructure, and describes the recent development of detection technologies against those cyberattacks.-
dc.languageeng-
dc.relation.ispartofSmart Cities and Homes: Key Enabling Technologies-
dc.subjectAdvanced metering infrastructure-
dc.subjectCybersecurity-
dc.subjectElectricity-pricing manipulation-
dc.subjectPartially observable Markov decision process-
dc.subjectSingle event detection-
dc.subjectSmart home scheduling-
dc.titleSmart home scheduling and cybersecurity: Fundamentals-
dc.typeBook_Chapter-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/B978-0-12-803454-5.00010-9-
dc.identifier.scopuseid_2-s2.0-84987899017-
dc.identifier.spage191-
dc.identifier.epage217-

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