Anomaly analysis on an open DNS dataset1

Benjamin Aziz, N Menychtas , Ammar Al Bazi

Research output: Working paper/PreprintPreprint

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Abstract

The increasing availability of open data and the demand to understand better the nature of anomalies and the causes underlying them in modern systems is encouraging researchers to analyse open datasets in various ways. These include both quantitative and qualitative methods. We show here how quantitative methods, such as timeline, local averages and exponentially weighted moving average analyses, led in this work to the discovery of three anomalies in a large open DNS dataset published by the Los Alamos National Laboratory.
Original languageEnglish
PublisherPeerJ
Number of pages7
DOIs
Publication statusPublished - 14 Aug 2018

Publication series

NamePeerJ Preprints
PublisherPeerJ
ISSN (Print)2167-9843

Bibliographical note

PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.27116v1 | CC BY 4.0 Open Access | rec: 14 Aug 2018, publ: 14 Aug 2018

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