Intrusion Detection Method of Electric Power Information Network in Cloud Computing Environment
| Autor: | Jiaqi Zhang, Guoping Feng, Dexi Zhou, Mingjiu Li |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 2113:012050 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/2113/1/012050 |
| Popis: | With the widespread application of power grid systems, the information security problems faced by power grids have become more obvious. Various internal and external intrusion attacks that occur frequently have become an important issue affecting the normal operation of power generation and operations. The purpose of this paper is to study the intrusion detection method of electric power information(PI) network in the cloud computing environment. With the help of the cloud platform’s ability to process big data, and based on the analysis of the PI network structure, a DBN optimized BP network algorithm is proposed, and the optimized BP neural network is used as a runtime classification program. Experimental results show that MR-DBN-BP has a detection rate of 96.7% for intrusion detection of PI networks, which can effectively detect intrusions and effectively protect the power dispatch system network. |
| Databáze: | OpenAIRE |
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