A big data based flow anomaly detection mechanism of electric power information network
With the construction of smart grid, the electric power information network and its business system get rapid development. The early flow anomaly detection and warning are significant to the safety of network. Due to the lack of efficient measuring means to handle the flow abnormal problems, a flow...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2017-03-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017031/ |
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| Summary: | With the construction of smart grid, the electric power information network and its business system get rapid development. The early flow anomaly detection and warning are significant to the safety of network. Due to the lack of efficient measuring means to handle the flow abnormal problems, a flow anomaly detection mechanism based on big data for the electric power information network was proposed. Through the comparative analysis of two common anomaly detection algorithms, the improved local outlier factor algorithm (M-LOF) and the support vector data description (SVDD) algorithm, the suitable flow anomaly detection method for electric power information network was summarized. |
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| ISSN: | 1000-0801 |