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Meeting Requirements Imposed by Secure Software Development Standards and Still Remaining Agile Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Visualization-Driven Approach to Anomaly Detection in the Movement of Critical Infrastructure

Authors : Evgenia Novikova, Ivan Murenin

Published in: Computer Network Security

Publisher: Springer International Publishing

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Abstract

Detection of anomalies in employees’ movement represents an area of considerable interest for cyber-physical security applications. In the paper the visual analytics approach to detection of the spatiotemporal patterns and anomalies in organization stuff movement is proposed. The key elements of the approach are interactive self-organizing maps used to detect groups of employees with similar behavior and heat map applied to detect anomalies. They are supported by a set of the interactive interconnected visual models aimed to present spatial and temporal route patterns. We demonstrate our approach with an application to the VAST MiniChallenge-2 2016 data set, which describes movement of the employees within organization building.

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previous chapter Extending FAST-CPS for the Analysis of Data Flows in Cyber-Physical Systems
next chapter Detection and Mitigation of Time Delay Injection Attacks on Industrial Control Systems with PLCs
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Metadata
Title
Visualization-Driven Approach to Anomaly Detection in the Movement of Critical Infrastructure
Authors
Evgenia Novikova
Ivan Murenin
Copyright Year
2017
Book
Computer Network Security

Print ISBN: 978-3-319-65126-2

Electronic ISBN: 978-3-319-65127-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-65127-9_5

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