Detecting anomalies in dynamic networks

Ranga Suri, NNR and Murty M, N and Athithan, G (2019) Detecting anomalies in dynamic networks. [Book Chapter]

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Abstract

This chapter deals with an important analysis task over dynamic networks, namely exploring the time varying characteristics of anomalies present in such networks. In this direction, a graph mining based framework is considered that takes a sequence of network snapshots as input for analysis. It defines various categories of temporal anomalies typically encountered in such an exploration and characterizes them appropriately to enable their detection. An experimental study of this framework over benchmark graph data sets is presented here to demonstrate the evolving behavior of the anomalies detected as per the categories defined.

Item Type:	Book Chapter
Publication:	Intelligent Systems Reference Library
Publisher:	Springer Science and Business Media Deutschland GmbH
Additional Information:	The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH.
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	18 Nov 2022 09:39
Last Modified:	18 Nov 2022 09:39
URI:	https://eprints.iisc.ac.in/id/eprint/77998

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