Evaluating Statistical Models for Network Traffic Anomaly Detection-Reference-Cited by-同舟云学术

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Evaluating Statistical Models for Network Traffic Anomaly Detection

Published:2019-04 Issue: Volume: Page:
ISSN:
Container-title:2019 Systems and Information Engineering Design Symposium (SIEDS)
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Author:

Kromkowski Peter,Li Shaoran,Zhao Wenxi,Abraham Brendan,Osborne Austin,Brown Donald E.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8726922/8735585/08735594.pdf?arnumber=8735594

Cited by 14 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. Detecting Stimuli with Novel Temporal Patterns to Accelerate Functional Coverage Closure;2024 IEEE International Test Conference in Asia (ITC-Asia);2024-08-18

2. Curriculum Learning-Based Multivariate Time Series Anomaly Detection;2024 35th Conference of Open Innovations Association (FRUCT);2024-04-24

3. Unlocking Deeper Understanding: Leveraging Explainable AI for API Anomaly Detection Insights;Proceedings of the 2024 16th International Conference on Machine Learning and Computing;2024-02-02

4. Application of Intelligent Methods of Correlation of System Events in Predictive Analysis of Security States of Objects of Critical Infrastructure;Pattern Recognition and Image Analysis;2023-09

5. Adversarial Learning Aided Malicious Network Traffic Detection Based on EDE Framework;2023 IEEE/CIC International Conference on Communications in China (ICCC);2023-08-10

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