Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network

With the emergence of spot electricity trading, market-oriented trading has been intensively carried out, forming a multi-cycle trading system. In this process, a large amount of fine-grained electricity trading data circulates on the trading platform. Trading data is an important basis for decision...

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Main Authors: Xi Luo, Letian He, Xiao Wei, Mao Zhu, Zhiyi Li
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723004419
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author Xi Luo
Letian He
Xiao Wei
Mao Zhu
Zhiyi Li
author_facet Xi Luo
Letian He
Xiao Wei
Mao Zhu
Zhiyi Li
author_sort Xi Luo
collection DOAJ
description With the emergence of spot electricity trading, market-oriented trading has been intensively carried out, forming a multi-cycle trading system. In this process, a large amount of fine-grained electricity trading data circulates on the trading platform. Trading data is an important basis for decision-making in the electricity spot market, which directly affects the trading profits of market entities, proper disclosure of this information is very important for market enterprises. Information disclosure must ensure the validity and security. However, it is hard to judge the security demand for trading data, and there is no suitable evaluation system for determining the security requirement of data, which will limit the electricity market’s further development. In this paper, we first design an indicator system for security requirements classification, which manages data risks from three aspects: data classification, data risk, and entity demand. This system will guide us in determining data security requirements and further help identify differentiated data security protection schemes. Then, based on this system, we propose the classification method of data security requirements through a hierarchical fuzzy Petri net. The lower network realizes a reasonable assessment of data risk with reference to the index system, and the upper network finally determines the level of security requirements through the fuzzy rule base. Last, two types of data are selected to judge their security requirements. The results show that our method can provide a reference for privacy protection in electricity market data.
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spelling doaj.art-c149140360d0459c92e6f362d77f7dd72023-09-06T04:51:40ZengElsevierEnergy Reports2352-48472023-09-019189199Security requirement classification of electricity trading data based on hierarchical fuzzy Petri networkXi Luo0Letian He1Xiao Wei2Mao Zhu3Zhiyi Li4Technical Section, Zhejiang Power Exchange Center, Zhejiang 310000, ChinaTechnical Section, Zhejiang Power Exchange Center, Zhejiang 310000, ChinaTechnical Section, Zhejiang Power Exchange Center, Zhejiang 310000, ChinaSchool of Electrical Engineering, Zhejiang University, Zhejiang 310012, China; Corresponding author.School of Electrical Engineering, Zhejiang University, Zhejiang 310012, ChinaWith the emergence of spot electricity trading, market-oriented trading has been intensively carried out, forming a multi-cycle trading system. In this process, a large amount of fine-grained electricity trading data circulates on the trading platform. Trading data is an important basis for decision-making in the electricity spot market, which directly affects the trading profits of market entities, proper disclosure of this information is very important for market enterprises. Information disclosure must ensure the validity and security. However, it is hard to judge the security demand for trading data, and there is no suitable evaluation system for determining the security requirement of data, which will limit the electricity market’s further development. In this paper, we first design an indicator system for security requirements classification, which manages data risks from three aspects: data classification, data risk, and entity demand. This system will guide us in determining data security requirements and further help identify differentiated data security protection schemes. Then, based on this system, we propose the classification method of data security requirements through a hierarchical fuzzy Petri net. The lower network realizes a reasonable assessment of data risk with reference to the index system, and the upper network finally determines the level of security requirements through the fuzzy rule base. Last, two types of data are selected to judge their security requirements. The results show that our method can provide a reference for privacy protection in electricity market data.http://www.sciencedirect.com/science/article/pii/S2352484723004419Fuzzy petri networkSecurity requirementElectricity trading dataRisk assessmentFuzzy rule
spellingShingle Xi Luo
Letian He
Xiao Wei
Mao Zhu
Zhiyi Li
Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
Energy Reports
Fuzzy petri network
Security requirement
Electricity trading data
Risk assessment
Fuzzy rule
title Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
title_full Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
title_fullStr Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
title_full_unstemmed Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
title_short Security requirement classification of electricity trading data based on hierarchical fuzzy Petri network
title_sort security requirement classification of electricity trading data based on hierarchical fuzzy petri network
topic Fuzzy petri network
Security requirement
Electricity trading data
Risk assessment
Fuzzy rule
url http://www.sciencedirect.com/science/article/pii/S2352484723004419
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