Automatic Classification of Quantitative Data from DNS Cache Servers into Stationary and Non-Stationary States Based on Clustering

Hikofumi Suzuki, Katsumi Wasaki

2023

Abstract

In this study, quantitative traffic data from DNS cache servers are classified as stationary or non-stationary. Then, unsupervised machine learning is performed using the classified traffic data. Among the 17 types of DNS traffic data subject to revision, A Record, MX, SOA Record, and AD Flag are considered. The correlation between A Record and AD Flag is difficult to detect using conventional clustering methods because they form zonal clusters under stationary-state conditions. Therefore, the number of clusters is calculated using the clustering algorithms Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Mean Shift, and variational Bayesian Gaussian mixture model (VBGMM). The possibility of automatic classification is investigated.

Paper Citation

in Harvard Style

Suzuki H. and Wasaki K. (2023). Automatic Classification of Quantitative Data from DNS Cache Servers into Stationary and Non-Stationary States Based on Clustering. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 319-326. DOI: 10.5220/0012082000003541

in Bibtex Style

@conference{data23,
author={Hikofumi Suzuki and Katsumi Wasaki},
title={Automatic Classification of Quantitative Data from DNS Cache Servers into Stationary and Non-Stationary States Based on Clustering},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={319-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012082000003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Automatic Classification of Quantitative Data from DNS Cache Servers into Stationary and Non-Stationary States Based on Clustering
SN - 978-989-758-664-4
AU - Suzuki H.
AU - Wasaki K.
PY - 2023
SP - 319
EP - 326
DO - 10.5220/0012082000003541
PB - SciTePress