Kaya, Muhammed Onur and Ozdem, Mehmet and Das, Resul (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.
![[thumbnail of 72157.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "72157.pdf")
PDF
72157.pdf
Download (2MB)
Abstract
This paper presents a novel approach for real-time anomaly detection and visualization of dynamic network data using Wireshark, globally's most widely utilized network analysis tool. As the complexity and volume of network data continue to grow, effective anomaly detection has become essential for m
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 18:31 |
| Last Modified: | 10 Apr 2026 22:58 |
| URI: | http://eprints.eai.eu/id/eprint/52826 |
Actions (login required)
- View Item