A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark

Muhammed Onur Kaya, Mehmet Ozdem, Resul Das

Open source

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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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

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