AI-Based Anomaly Detection and Classification of Traffic Using Netflow

Gustavo Granadillo; Nesrine Kaaniche

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Paper

AI-Based Anomaly Detection and Classification of Traffic Using Netflow

Topics: Artificial Intelligence for Security and Privacy; Intrusion Detection & Prevention; Machine learning applications to data security and privacy; Machine Learning Security and Privacy; Security and Privacy for Artificial Intelligence

In Proceedings of the 22nd International Conference on Security and Cryptography SECRYPT - Volume 1, 644-649, 2025 , Bilbao, Spain

Authors: Gustavo Gonzalez Granadillo ¹ and Nesrine Kaaniche ²

Affiliations: ¹ Schneider Electric, DCR Security Department, Barcelona, Spain ; ² SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris, France

Keyword(s): Anomaly Detection, Network Traffic Behavior, Classification Algorithms, NetFlow.

Abstract: Anomalies manifest differently in network statistics, making it difficult to develop generalized models for normal network behaviors and anomalies. This paper analyzes various Machine Learning (ML) and Deep Learning (DL) algorithms employing supervised techniques for both binary and multi-class classification of network traffic. Experiments have been conducted using a validated NetFlow-based dataset containing over 31 million incoming and outgoing network connections of an IT infrastructure. Preliminary results indicate that no single model effectively detects all cyber-attacks. However, selected models for binary and multi-class classification show promising results, achieving performance levels of up to 99.9% in the best of the cases.

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Paper citation in several formats:

Granadillo, G. G., Kaaniche and N. (2025). AI-Based Anomaly Detection and Classification of Traffic Using Netflow. In Proceedings of the 22nd International Conference on Security and Cryptography - SECRYPT; ISBN 978-989-758-760-3; ISSN 2184-7711, SciTePress, pages 644-649. DOI: 10.5220/0013552700003979

@conference{secrypt25,
author={Gustavo Gonzalez Granadillo and Nesrine Kaaniche},
title={AI-Based Anomaly Detection and Classification of Traffic Using Netflow},
booktitle={Proceedings of the 22nd International Conference on Security and Cryptography - SECRYPT},
year={2025},
pages={644-649},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013552700003979},
isbn={978-989-758-760-3},
issn={2184-7711},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Security and Cryptography - SECRYPT
TI - AI-Based Anomaly Detection and Classification of Traffic Using Netflow
SN - 978-989-758-760-3
IS - 2184-7711
AU - Granadillo, G.
AU - Kaaniche, N.
PY - 2025
SP - 644
EP - 649
DO - 10.5220/0013552700003979
PB - SciTePress