Analysis of Machine Learning-Based Methods for Network Traffic Anomaly Detection and Prediction

Jingyao Wang

2025

Abstract

In the era of rapid development of network technology, the volume of network data traffic has grown exponentially. Network traffic analysis and prediction can effectively facilitate network management, enable timely detection of network attacks, and enhance security protection and optimization of internet resources. This paper introduces the current application of machine learning in network traffic anomaly detection and prediction, along with key technologies such as data preprocessing, feature engineering, model evaluation, and optimization. It describes the technological advancements in traditional machine learning and deep learning methods for traffic classification, anomaly detection, and traffic prediction. The paper highlights the challenges faced by machine learning in network traffic analysis and prediction, including data complexity, real-time processing, and privacy protection. To address these challenges, machine learning in network traffic analysis and detection will rely on interdisciplinary collaboration and technological innovation to develop more automated, intelligent models that emphasize privacy protection, model interpretability, and real-time processing capabilities.

Paper Citation

in Harvard Style

Wang J. (2025). Analysis of Machine Learning-Based Methods for Network Traffic Anomaly Detection and Prediction. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 550-554. DOI: 10.5220/0013701800004670

in Bibtex Style

@conference{icdse25,
author={Jingyao Wang},
title={Analysis of Machine Learning-Based Methods for Network Traffic Anomaly Detection and Prediction},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={550-554},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013701800004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Analysis of Machine Learning-Based Methods for Network Traffic Anomaly Detection and Prediction
SN - 978-989-758-765-8
AU - Wang J.
PY - 2025
SP - 550
EP - 554
DO - 10.5220/0013701800004670
PB - SciTePress