A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark
- DOI
- 10.4108/eetinis.v12i2.7616
- Published
- 2025-01-07
- Container
- EAI Endorsed Transactions on Industrial Networks and Intelligent Systems
- Publisher
- European Alliance for Innovation n.o.
- Open access
- unknown
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uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.4108/eetinis.v12i2.7616,
title = {A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark},
author = {Muhammed Onur Kaya and Mehmet Ozdem and Resul Das},
year = {2025},
journal = {EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
doi = {10.4108/eetinis.v12i2.7616},
url = {https://doi.org/10.4108/eetinis.v12i2.7616}
}RIS
TY - JOUR TI - A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark AU - Muhammed Onur Kaya AU - Mehmet Ozdem AU - Resul Das PY - 2025 JO - EAI Endorsed Transactions on Industrial Networks and Intelligent Systems DO - 10.4108/eetinis.v12i2.7616 UR - https://doi.org/10.4108/eetinis.v12i2.7616 ER -
APA
Kaya, M. O., Ozdem, M., & Das, R. (2025). A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems. https://doi.org/10.4108/eetinis.v12i2.7616
Source records
- crossref · retrieved 2026-09-26T13:48:27.386Z