Anomaly Detection Model for Data Interactions Based on Temporal Features in Electric Power Data Centers-Reference-Cited by-同舟云学术

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Anomaly Detection Model for Data Interactions Based on Temporal Features in Electric Power Data Centers

Published:2023-11-17 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Communication, Image and Signal Processing (CCISP)
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Author:

Yu Pengfei¹,Zhou Xiaoming²,Chen Longdan³,Qi Jun⁴,Bai Liang⁴

Affiliation:

1. State Grid Smart Grid Research Institute Co.,LTD,State Grid Laboratory of Power cyber-Security, Protection and Monitoring Technology,Nanjing,China

2. State Grid Liaoning Electric, Power Supply Company Limited,Shenyang,Liaoning,China

3. Beijing University Of Posts and Telecommunications,Beijing,China

4. State Grid Liaoning Electric Power Supply Co.,LTD., Information & Telecommunication Branch,Shenyang,Liaoning,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10355681/10355682/10355803.pdf?arnumber=10355803

Reference20 articles.

1. Construction of Data Unified Model for Mid-platform Architecture in Power Grid [J];Liu;Information Technology,2023

2. Machine Learning-based Method for Detection and Classification of Network Anomalies in Power Systems [J];Duan;Automation and Instrumentation,2023

3. Research on Anomaly Detection Methods for Multi-variate Time Series Data [D];Chen;Advisor: Zou Chengming. Wuhan University of Technology,2021

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