Publikation: Finding Anomalies in Time-Series using Visual Correlation for Interactive Root Cause Analysis
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2013
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Proceedings of the Tenth Workshop on Visualization for Cyber Security - VizSec '13. New York, New York, USA: ACM Press, 2013, pp. 65-72. ISBN 978-1-4503-2173-0. Available under: doi: 10.1145/2517957.2517966
Zusammenfassung
Monitoring computer networks often includes gathering vast amounts of time-series data from thousands of computer systems and network devices. Threshold alerting is easy to accomplish with state-of-the-art technologies. However, to find correlations and similar behaviors between the different devices is challenging. We developed a visual analytics application to tackle this challenge by integrating similarity models and analytics combined with well-known, but task-adapted, time-series visualizations. We show in a case study, how this system can be used to visually identify correlations and anomalies in large data sets and identify and investigate security-related events.
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the Tenth Workshop, 14. Okt. 2013 - 14. Okt. 2013, Atlanta, Georgia
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STOFFEL, Florian, Fabian FISCHER, Daniel A. KEIM, 2013. Finding Anomalies in Time-Series using Visual Correlation for Interactive Root Cause Analysis. the Tenth Workshop. Atlanta, Georgia, 14. Okt. 2013 - 14. Okt. 2013. In: Proceedings of the Tenth Workshop on Visualization for Cyber Security - VizSec '13. New York, New York, USA: ACM Press, 2013, pp. 65-72. ISBN 978-1-4503-2173-0. Available under: doi: 10.1145/2517957.2517966BibTex
@inproceedings{Stoffel2013Findi-26514,
year={2013},
doi={10.1145/2517957.2517966},
title={Finding Anomalies in Time-Series using Visual Correlation for Interactive Root Cause Analysis},
isbn={978-1-4503-2173-0},
publisher={ACM Press},
address={New York, New York, USA},
booktitle={Proceedings of the Tenth Workshop on Visualization for Cyber Security - VizSec '13},
pages={65--72},
author={Stoffel, Florian and Fischer, Fabian and Keim, Daniel A.}
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