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- Publisher Website: 10.1016/B978-0-12-803454-5.00010-9
- Scopus: eid_2-s2.0-84987899017
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Book Chapter: Smart home scheduling and cybersecurity: Fundamentals
Title | Smart home scheduling and cybersecurity: Fundamentals |
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Authors | |
Keywords | Advanced metering infrastructure Cybersecurity Electricity-pricing manipulation Partially observable Markov decision process Single event detection Smart home scheduling |
Issue Date | 2016 |
Citation | Smart Cities and Homes: Key Enabling Technologies, 2016, p. 191-217 How to Cite? |
Abstract | The 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 Identifier | http://hdl.handle.net/10722/336165 |
DC Field | Value | Language |
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dc.contributor.author | Liu, Y. | - |
dc.contributor.author | Hu, S. | - |
dc.date.accessioned | 2024-01-15T08:24:05Z | - |
dc.date.available | 2024-01-15T08:24:05Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Smart Cities and Homes: Key Enabling Technologies, 2016, p. 191-217 | - |
dc.identifier.uri | http://hdl.handle.net/10722/336165 | - |
dc.description.abstract | The 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.language | eng | - |
dc.relation.ispartof | Smart Cities and Homes: Key Enabling Technologies | - |
dc.subject | Advanced metering infrastructure | - |
dc.subject | Cybersecurity | - |
dc.subject | Electricity-pricing manipulation | - |
dc.subject | Partially observable Markov decision process | - |
dc.subject | Single event detection | - |
dc.subject | Smart home scheduling | - |
dc.title | Smart home scheduling and cybersecurity: Fundamentals | - |
dc.type | Book_Chapter | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/B978-0-12-803454-5.00010-9 | - |
dc.identifier.scopus | eid_2-s2.0-84987899017 | - |
dc.identifier.spage | 191 | - |
dc.identifier.epage | 217 | - |