TY - GEN
T1 - AI-Based Anomaly Detection and Classification of Traffic Using Netflow
AU - Granadillo, Gustavo Gonzalez
AU - Kaaniche, Nesrine
N1 - Publisher Copyright:
© 2025 by Paper published under CC license (CC BY-NC-ND 4.0).
PY - 2025/1/1
Y1 - 2025/1/1
N2 - 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.
AB - 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.
KW - Anomaly Detection
KW - Classification Algorithms
KW - NetFlow
KW - Network Traffic Behavior
UR - https://www.scopus.com/pages/publications/105010458374
U2 - 10.5220/0013552700003979
DO - 10.5220/0013552700003979
M3 - Conference contribution
AN - SCOPUS:105010458374
SN - 9789897587603
T3 - Proceedings of the International Conference on Security and Cryptography
SP - 644
EP - 649
BT - Proceedings of the 22nd International Conference on Security and Cryptography, SECRYPT 2025
A2 - De Capitani Di Vimercati, Sabrina
A2 - Samarati, Pierangela
PB - Science and Technology Publications, Lda
T2 - 22nd International Conference on Security and Cryptography, SECRYPT 2025
Y2 - 11 June 2025 through 13 June 2025
ER -