A Distributed Online Learning Approach to Detect Anomalies for Virtualized Network Slicing
Author:
Affiliation:
1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications,Chongqing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9685019/9685006/09685997.pdf?arnumber=9685997
Reference18 articles.
1. Online Internet Anomaly Detection With High Accuracy: A Fast Tensor Factorization Solution
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4. 5G-TRANSFORMER: Slicing and Orchestrating Transport Networks for Industry Verticals
5. Consensus-based dis-tributed support vector machines;forero;J Mach Learn Res,2010
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1. A Survey of Graph-Based Deep Learning for Anomaly Detection in Distributed Systems;IEEE Transactions on Knowledge and Data Engineering;2024-01
2. Consensus-Based Distributed Kernel One-class Support Vector Machine for Anomaly Detection;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18
3. Distributed Online Anomaly Detection for Virtualized Network Slicing Environment;IEEE Transactions on Vehicular Technology;2022-11
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