Cloud Based Big Data DNS Analytics at Turknet
Altan Cakir, Yousef Alkhanafseh, Esra Karabiyik, Erhan Kurubas, Rabia, Burcu Bunyak, Cenk Anil Bahcevan

TL;DR
This paper presents a cloud-based big data analytics platform using Apache Spark to analyze DNS traffic, enabling pattern detection and domain grouping for improved business intelligence.
Contribution
It introduces a novel cloud-based big data application for DNS traffic analysis utilizing Spark, with a focus on pattern detection and domain grouping.
Findings
Effective domain grouping based on traffic patterns
Preliminary results demonstrate utility in business intelligence
Scalable analysis of DNS data in real-time
Abstract
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…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · IPv6, Mobility, Handover, Networks, Security · Energy Efficient Wireless Sensor Networks
