Change Detection in Large Evolving Networks
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Author/Creator
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Date
2019-04
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Citation of Original Publication
Josephine M. Namayanja, Vandana P. Janeja, Change Detection in Large Evolving Networks, International Journal of Data Warehousing and Mining, Volume 15 , Issue 2 ,April-June 2019, DOI: 10.4018/IJDWM.2019040104
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© IGI Global
© IGI Global
Abstract
This article presents a novel technique for the detection of change in massive evolving communication
networks. This approach utilizes a novel hybrid sampling methodology to select central nodes and
key subgraphs from networks over time. The objective is to select and utilize a much smaller targeted
sample of the network, represented as a graph, without loss of any knowledge derived from graph
properties as compared to the entire massive graph. This article uses the targeted samples to detect
micro- and macro-level changes in the network. This approach can be potentially useful in the domain
of cybersecurity where this article highlights the importance of graph sampling and multi-level
change detection in identifying network changes that may be difficult to detect on a larger scale.
This article therefore presents a means to audit large networks to establish continuous awareness of
network behavior.