Domain Name System (DNS) is a hierarchical distributed naming system for computers, services, or any resource connected to the Internet. A DNS resolves queries for URLs into IP addresses for the purpose of locating computer services and devices worldwide. As of now, analytical applications with a vast amount of DNS data are a challenging problem. Clustering the features of domain traffic from a DNS data has given necessity to the need for more sophisticated analytics platforms and tools because of the sensitivity of the data characterization. In this study, a cloud based big data application, based on Apache Spark, on DNS data is proposed, as well as a periodic trend pattern based on traffic to partition numerous domain names and region into separate groups by the characteristics of their query traffic time series. Preliminary experimental results on a Turknet DNS data in daily operations are discussed with business intelligence applications.
CITATION STYLE
Çakır, A., Alkhanafseh, Y., Karabıyık, E., Kurubaş, E., Bunyak, R. B., & Bahçevan, C. A. (2021). Cloud Based Big Data DNS Analytics at Turknet. In Advances in Intelligent Systems and Computing (Vol. 1197 AISC, pp. 833–841). Springer. https://doi.org/10.1007/978-3-030-51156-2_96
Mendeley helps you to discover research relevant for your work.