Towards Building Network Outlier Detection System for Network Traffic Monitoring
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F25%3A00384331" target="_blank" >RIV/68407700:21240/25:00384331 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/NOMS57970.2025.11073727" target="_blank" >https://doi.org/10.1109/NOMS57970.2025.11073727</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NOMS57970.2025.11073727" target="_blank" >10.1109/NOMS57970.2025.11073727</a>
Alternative languages
Result language
angličtina
Original language name
Towards Building Network Outlier Detection System for Network Traffic Monitoring
Original language description
Traffic monitoring is important for supporting network security and management. Recent advancements have explored machine learning-based approaches to classify encrypted traffic, yet the challenge of obtaining current threat datasets persists, leaving supervised models reliant on outdated information. Outlier detection, which identifies anomalous network behavior without requiring labeled data, addresses this limitation by flagging suspicious deviations from expected patterns. This paper proposes a novel Network Outlier Detection System (NODS), a platform based on open-source software designed to detect outliers in network traffic by leveraging forecasting models. Our system was deployed and tested on a large ISP infrastructure. The evaluation of detected outliers over a one-month period showed key insights into system performance and provided valuable lessons for future deployment of outlier detection methods. This paper details the architecture of NODS, deployment, and performance while highlighting the challenges and lessons learned in building an effective outlier detection system for network traffic.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/VJ02010024" target="_blank" >VJ02010024: Flow-based Encrypted Traffic Analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
NOMS 2025-2025 IEEE Network Operations and Management Symposium
ISBN
979-8-3315-3163-8
ISSN
2374-9709
e-ISSN
—
Number of pages
6
Pages from-to
—
Publisher name
IEEE
Place of publication
New York
Event location
Honolulu
Event date
May 12, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001556086900153