Anomaly prediction in network traffic using adaptive Wiener filtering and ARMA modeling
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx5/4803719/4811240/04811848.pdf?arnumber=4811848
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Assessment of Machine-Learning-Based Traffic Prediction Algorithms for Real Access/Metro Network Traffic;2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM);2023-11-04
2. Spatiotemporal-Enhanced Recurrent Neural Network for Network Traffic Prediction;2023 IEEE Symposium on Computers and Communications (ISCC);2023-07-09
3. Deep Learning Based Traffic Prediction Method for Digital Twin Network;Cognitive Computation;2023-05-27
4. Building a Forecast Using a Linear Prediction Filter for the Purpose of Detecting Anomalies in the Signals of Automated Process Control Systems;2023 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM);2023-05-15
5. Proposal and comparison of network anomaly detection based on long-memory statistical models;Logic Journal of IGPL;2016-08-09
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